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Experience:
2 years required
Skills:
Python, SQL, Tableau, Quantitative Analysis
Job type:
Full-time
Salary:
negotiable
- Understanding of business problems forgathering/analyzing/designing the data to solve the problems from end-to-end process.
- Excellent in written and verbal communication skills for coordinating across teams.
- Analyze large amounts of information to discover trends and patterns.
- Lead the analytics group in management of projects and experiment designing, implementing innovative Predictive Models, implementing innovative analytic solutions or driving outstanding results.
- Proficient in common data science toolkits (R, Python) and using SQL languages.
- Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop).
- Good applied statistics skills, such as distributions, statistical testing, regression, etc.
- At least 2-3 year in Business Intelligence/Data Analytic.
- Proficiency in statistical analysis, quantitative analytic, forecasting/predictive analytic, experimental design and optimization algorithms.
- Technical expertise regarding data modeling, data mining, segmentation techniques, unstructured data skills, and other data science.
- Programming skills in big data frameworks and statistical modeling such as SAS, R, and Python, CE Techniques.
- Experience in data visualization tools.
- Knowledge/experience in machine learning.
- Domain knowledge of mobile, network and telecommunication technology and services would be advantageous.
Skills:
Project Management, SQL, Python, English
Job type:
Full-time
Salary:
negotiable
- Adjust language models that have already been trained for generative AI applications Ensure that the LLMs and pipelines based on LLMs are tuned and released.
- Create and implement LLMs for various content creation jobs Develop and communicate roadmaps for data science projects.
- Design effective agile workflows and manage a cycle of deliverables that meet timeline and resource constraints.
- Serve as a bridge between stakeholders and AI suppliers to facilitate seamless communication and understanding of project requirements.
- Work closely with external AI suppliers to ensure alignment between project goals and technological capabilities.
- Identify and gather data sets necessary for AI projects.
- Prior experience in Machine Learning, Deep Learning, and AI algorithm to solve respective business cases and pain points.
- Prior hands-on experience in data-mining techniques to better understand each pain point and provide insights.
- Able to design and conduct analysis to support product & channel improvement and development.
- Present key findings and recommendations to business counter parties and senior management on project approach and strategic planning.
- Bachelor degree or higher in Computer Science, Computer Engineering, Information Technology, Management Information System or an IT related field.
- Native Thai speaker & fluent in English.
- 3+ years of proven experience as a Data Scientist with a focus on project management (Retail or E-Commerce business is preferable).
- At least 2+ years of relevant experience as an LLM Data Scientist Experience in SQL and Python (Pandas, Numpy, SparkSQL).
- Ability to manipulate and analyze complex, high-volume, high-dimensionality data from varying sources.
- Experience in Big Data Technologies like Hadoop, Apache Spark, Databrick.
- Experience in machine learning and deep learning (Tensorflow, Keras, Scikit-learn).
- Good Knowledge of Statistics.
- Experience in Data Visualization (Tableau, PowerBI) is a plus.
- Excellent communication skills with the ability to convey complex findings to non-technical stakeholders.
- Having good attitude toward team working and willing to work hard.
Skills:
Research, Statistics, Python, English
Job type:
Full-time
Salary:
negotiable
- Apply statistical and machine learning methods to large, complex data sets to draw insights and provide actionable recommendations.
- Solve complex problems on both technical and business sides using advanced analytical methods.
- Work with Engineering teams to implement end-to-end process from model development to testing, validation, and deployment.
- Research and develop new quantitative models and frameworks to enhance the company s data science capability.
- Basic Qualifications Bachelor s degree in Engineering, Computer Science, Math, Physics, Statistics or other areas that are highly quantitative.
- Experience with statistical programming languages (e.g., Python, R, pandas) and database software (e.g., SQL, PySpark).
- Knowledge in statistics (e.g., hypothesis testing, regression) and machine learning.
- Strong analytical problem-solving capabilities.
- Preferred Qualifications Master s or PhD degree in a quantitative discipline.
- Experience applying machine learning and statistical methods to large datasets.
- Solid understanding of advanced statistics and machine learning practices.
- Experience in one or more specialized machine learning areas (e.g., NLP, deep learning, recommendation systems, reinforcement learning).
- Outstanding coding skills or software development background.
- Ability to think independently and communicate complex ideas to less technical persons.
- Excellent command of English in both verbal and written forms.
- We're committed to bringing passion and customer focus to the business. If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us.
Skills:
SQL, Javascript, Research
Job type:
Full-time
Salary:
āļŋ45,000 - āļŋ55,000, negotiable
- Manage and maintain large datasets related to affiliate operations, ensuring data accuracy and integrity.
- Develop, optimize, and execute SQL queries to extract, manipulate, and analyze data for reporting and strategic planning.
- Use JavaScript, HTML, and CSS to design, implement, and enhance data visualization tools and dashboards.
- Provide in-depth analysis of affiliate program performance, identifying trends and recommending actionable strategies.
- Collaborate with internal teams (key account, campaign marketing, commercial, product) to define metrics, set KPIs, and support data-driven decisions.
- Automate routine reporting tasks and build dynamic dashboards to streamline affiliate program monitoring.
- Research and resolve data discrepancies, ensuring reliable and consistent reporting across the organization.
- Monitor the performance of affiliate campaigns and provide recommendations to improve effectiveness.
- Stay updated with the latest tools and technologies for data analysis and reporting to implement best practices.
- 4-5 years of experience in a data analysis role, preferably within an e-commerce or affiliate marketing environment.
- Advanced proficiency in SQL for data extraction, manipulation, and analysis.
- Hands-on experience with JavaScript, HTML, and CSS for data visualization and dashboard creation.
- Strong understanding of data management, reporting, and analytics tools.
- Proven ability to analyze complex datasets and provide clear, actionable insights.
- Detail-oriented, with excellent problem-solving and critical-thinking skills.
- Effective communication skills to present findings and recommendations to non-technical stakeholders.
- Experience with data visualization platforms like Tableau, Power BI, or Google Data Studio.
- Ability to work independently and as part of a team in a fast-paced environment.
Skills:
Sales, Marketing Strategy, Statistics
Job type:
Full-time
Salary:
negotiable
- Analyze consumer behavior, market trends, and competitor data, and provide data-driven recommendations for business expansion or marketing strategy development.
- Collect sales, operational, and marketing data from internal and external sources to assess the impact of marketing campaigns and forecast business opportunities.
- Update and maintain accurate databases, and create analytical reports (Dashboards) to present data to management.
- Coordinate with marketing, sales, and other departments to gather information for analysis and address the needs of the organization.
- Bachelor's degree or higher in Data Science, Marketing, Statistics, or a related field.
- At least 2-3 years of experience in data analysis. Experience in retail business will be considered an advantage.
- Proficiency in data analysis tools such as Excel, SQL, Power BI, Tableau, or Python.
- Strong analytical skills and the ability to solve problems in a systematic manner.
- Good presentation and communication skills to convey complex information clearly.
- Attention to detail and the ability to work under pressure.
Skills:
Power BI, Excel, Microsoft Office
Job type:
Full-time
Salary:
negotiable
- āļ§āļīāđāļāļĢāļēāļ°āļŦāđ āđāļĨāļ°āļāļąāļāļāļģāļĢāļēāļĒāļāļēāļāđāļāļĢāļĩāļĒāļāđāļāļĩāļĒāļāļāđāļāļĄāļđāļĨ āļāđāļēāļāđ āđāļāđāļ āļĢāļēāļĒāļ§āļąāļ, āļĢāļēāļĒāđāļāļ·āļāļ, āļĢāļēāļĒāļāļĩ āđāļāļĒāđāļāļĢāļĩāļĒāļāđāļāļĩāļĒāļāļāļąāļāļāđāļāļĄāļđāļĨāđāļāļāļāļĩāļāđāļāđāļēāļŦāļĄāļēāļĒ āđāļĨāļ°āļāļēāļĢāļāļĢāļ°āļĄāļēāļāļāļēāļĢāđāļāļāļāļēāļāļ āđāļāļ·āđāļāļāļģāđāļŠāļāļāļāļđāđāļāļĢāļīāļŦāļēāļĢ.
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- āļāļąāļāļāļģāļĢāļēāļĒāļāļēāļāļŠāļĢāļļāļ Profit & Loss āļāļĢāļ°āļāļģāđāļāļ·āļāļāđāļāļĄāļļāļĄāļĄāļāļāļāļĢāļīāļŦāļēāļĢāļŊ āđāļāļ·āđāļāļāļģāđāļŠāļāļāļāļđāđāļāļĢāļīāļŦāļēāļĢ.
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- āļāļāļāđāļāļ Template āđāļŦāđāļŠāđāļ§āļāļāļēāļāļāđāļēāļāđāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļ āđāļāļ·āđāļāļĢāļāļāļĢāļąāļāļāļēāļĢāļāļģāļāļēāļāđāļāļāļēāļĢāļĢāļ§āļāļĢāļ§āļĄāļāđāļāļĄāļđāļĨ āđāļāļ·āđāļāļāđāļ§āļĒāđāļŦāđāļāļēāļĢāļāļģāļāļēāļ āđāļāđāļāļĨāļĨāļąāļāļāđāļāļĩāđāļĢāļ§āļāđāļĢāđāļ§āļāļķāđāļ.
- āļ§āļīāđāļāļĢāļēāļ°āļŦāđāļāđāļāļĄāļđāļĨāļāļ·āđāļ āđ āļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļ āļāļēāļĄāļāļĩāđāđāļāđāļĢāļąāļāļĄāļāļāļŦāļĄāļēāļĒ.
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Skills:
Excel
Job type:
Full-time
Salary:
negotiable
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- āđāļāļĩāđāļĒāļ§āļāļēāļāļāļēāļĢāđāļāđ Microsoft Excel, Office, PowerPoint.
- āļĄāļĩāļāļ§āļēāļĄāļĨāļ°āđāļāļĩāļĒāļāļĢāļāļāļāļĢāļāļāđāļāļāļēāļĢāļāļģāļāļēāļāđāļĨāļ°āļĄāļĩāļāļ§āļēāļĄāļĢāļąāļāļāļīāļāļāļāļāđāļāļāļēāļĢāļāļģāļāļēāļ.
Experience:
3 years required
Skills:
Big Data, Hive, SAS
Job type:
Full-time
Salary:
negotiable
- Design, implement, and maintain data analytics pipelines and processing systems.
- Experience of data modelling techniques and integration patterns.
- Write data transformation jobs through code.
- Analyze large datasets to extract insights and identify trends.
- Perform data management through data quality tests, monitoring, cataloging, and governance.
- Knowledge in data infrastructure ecosystem.
- Collaborate with cross-functional teams to identify opportunities to leverage data to drive business outcomes.
- Build data visualizations to communicate findings to stakeholders.
- A willingness to learn and find solutions to complex problems.
- Stay up-to-date with the latest developments in data analytics and science.
- Experience migrating from on-premise data stores to cloud solutions.
- Knowledge of system design and platform thinking to build sustainable solution.
- Practical experience with modern and traditional Big Data stacks (e.g BigQuery, Spark, Databricks, duckDB, Impala, Hive, etc).
- Experience working with data warehouse solutions ELT solutions, tools, and techniques (e.g. Airflow, dbt, SAS, Matillion, Nifi).
- Experience with agile software delivery and CI/CD processes.
- Bachelor's or Master's degree in computer science, statistics, engineering, or a related field.
- At least 3 years of experience in data analysis and modeling.
- Proficiency in Python, and SQL.
- Experience with data visualization tools such as Tableau, Grafana or similar.
- Familiarity with cloud computing platforms, such as GCP, AWS or Databricks.
- Strong problem-solving skills and the ability to work independently as well as collaboratively.
- This role offers a clear path to advance into machine learning and AI with data quality and management, providing opportunities to work on innovative projects and develop new skills in these exciting fields..
- Contact: [email protected] (K.Thipwimon).
- āļāđāļēāļāļŠāļēāļĄāļēāļĢāļāļāđāļēāļāđāļĨāļ°āļĻāļķāļāļĐāļēāļāđāļĒāļāļēāļĒāļāļ§āļēāļĄāđāļāđāļāļŠāđāļ§āļāļāļąāļ§āļāļāļāļāļāļēāļāļēāļĢāļāļĢāļļāļāđāļāļĒ āļāļģāļāļąāļ (āļĄāļŦāļēāļāļ) āļāļĩāđ https://krungthai.com/th/content/privacy-policy āļāļąāđāļāļāļĩāđ āļāļāļēāļāļēāļĢāđāļĄāđāļĄāļĩāđāļāļāļāļēāļŦāļĢāļ·āļāļāļ§āļēāļĄāļāļģāđāļāđāļāđāļāđ āļāļĩāđāļāļ°āļāļĢāļ°āļĄāļ§āļĨāļāļĨāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļāđāļāļāđāļŦāļ§ āļĢāļ§āļĄāļāļķāļāļāđāļāļĄāļđāļĨāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļāļĻāļēāļŠāļāļēāđāļĨāļ°/āļŦāļĢāļ·āļāļŦāļĄāļđāđāđāļĨāļŦāļīāļ āļāļķāđāļāļāļēāļāļāļĢāļēāļāļāļāļĒāļđāđāđāļāļŠāļģāđāļāļēāļāļąāļāļĢāļāļĢāļ°āļāļģāļāļąāļ§āļāļĢāļ°āļāļēāļāļāļāļāļāļāđāļēāļāđāļāđāļāļĒāđāļēāļāđāļ āļāļąāļāļāļąāđāļ āļāļĢāļļāļāļēāļāļĒāđāļēāļāļąāļāđāļŦāļĨāļāđāļāļāļŠāļēāļĢāđāļāđ āļĢāļ§āļĄāļāļķāļāļŠāļģāđāļāļēāļāļąāļāļĢāļāļĢāļ°āļāļģāļāļąāļ§āļāļĢāļ°āļāļēāļāļ āļŦāļĢāļ·āļāļāļĢāļāļāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļāđāļāļāđāļŦāļ§āļŦāļĢāļ·āļāļāđāļāļĄāļđāļĨāļāļ·āđāļāđāļ āļāļķāđāļāđāļĄāđāđāļāļĩāđāļĒāļ§āļāđāļāļāļŦāļĢāļ·āļāđāļĄāđāļāļģāđāļāđāļāļŠāļģāļŦāļĢāļąāļāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāđāļāļāļēāļĢāļŠāļĄāļąāļāļĢāļāļēāļāđāļ§āđāļāļāđāļ§āđāļāđāļāļāđ āļāļāļāļāļēāļāļāļĩāđ āļāļĢāļļāļāļēāļāļģāđāļāļīāļāļāļēāļĢāđāļŦāđāđāļāđāđāļāļ§āđāļēāđāļāđāļāļģāđāļāļīāļāļāļēāļĢāļĨāļāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļāđāļāļāđāļŦāļ§ (āļāđāļēāļĄāļĩ) āļāļāļāļāļēāļāđāļĢāļāļđāđāļĄāđāđāļĨāļ°āđāļāļāļŠāļēāļĢāļāļ·āđāļāđāļāļāđāļāļāļāļĩāđāļāļ°āļāļąāļāđāļŦāļĨāļāđāļāļāļŠāļēāļĢāļāļąāļāļāļĨāđāļēāļ§āđāļ§āđāļāļāđāļ§āđāļāđāļāļāđāđāļĨāđāļ§āļāđāļ§āļĒ āļāļąāđāļāļāļĩāđ āļāļāļēāļāļēāļĢāļĄāļĩāļāļ§āļēāļĄāļāļģāđāļāđāļāļāđāļāļāđāļāđāļāļĢāļ§āļāļĢāļ§āļĄāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄāļāļāļāļāđāļēāļāđāļāļ·āđāļāļāļĢāļĢāļĨāļļāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāđāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāļĢāļąāļāļāļļāļāļāļĨāđāļāđāļēāļāļģāļāļēāļ āļŦāļĢāļ·āļāļāļēāļĢāļāļĢāļ§āļāļŠāļāļāļāļļāļāļŠāļĄāļāļąāļāļī āļĨāļąāļāļĐāļāļ°āļāđāļāļāļŦāđāļēāļĄ āļŦāļĢāļ·āļāļāļīāļāļēāļĢāļāļēāļāļ§āļēāļĄāđāļŦāļĄāļēāļ°āļŠāļĄāļāļāļāļāļļāļāļāļĨāļāļĩāđāļāļ°āđāļŦāđāļāļģāļĢāļāļāļģāđāļŦāļāđāļ āļāļķāđāļāļāļēāļĢāđāļŦāđāļāļ§āļēāļĄāļĒāļīāļāļĒāļāļĄāđāļāļ·āđāļāđāļāđāļāļĢāļ§āļāļĢāļ§āļĄ āđāļāđ āļŦāļĢāļ·āļāđāļāļīāļāđāļāļĒāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄāļāļāļāļāđāļēāļāļĄāļĩāļāļ§āļēāļĄāļāļģāđāļāđāļāļŠāļģāļŦāļĢāļąāļāļāļēāļĢāđāļāđāļēāļāļģāļŠāļąāļāļāļēāđāļĨāļ°āļāļēāļĢāđāļāđāļĢāļąāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāļāļēāļĄāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāļāļąāļāļāļĨāđāļēāļ§āļāđāļēāļāļāđāļ āđāļāļāļĢāļāļĩāļāļĩāđāļāđāļēāļāđāļĄāđāđāļŦāđāļāļ§āļēāļĄāļĒāļīāļāļĒāļāļĄāđāļāļāļēāļĢāđāļāđāļāļĢāļ§āļāļĢāļ§āļĄ āđāļāđ āļŦāļĢāļ·āļāđāļāļīāļāđāļāļĒāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄ āļŦāļĢāļ·āļāļĄāļĩāļāļēāļĢāļāļāļāļāļ§āļēāļĄāļĒāļīāļāļĒāļāļĄāđāļāļ āļēāļĒāļŦāļĨāļąāļ āļāļāļēāļāļēāļĢāļāļēāļāđāļĄāđāļŠāļēāļĄāļēāļĢāļāļāļģāđāļāļīāļāļāļēāļĢāđāļāļ·āđāļāļāļĢāļĢāļĨāļļāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāļāļąāļāļāļĨāđāļēāļ§āļāđāļēāļāļāđāļāđāļāđ āđāļĨāļ°āļāļēāļ āļāļģāđāļŦāđāļāđāļēāļāļŠāļđāļāđāļŠāļĩāļĒāđāļāļāļēāļŠāđāļāļāļēāļĢāđāļāđāļĢāļąāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāļĢāļąāļāđāļāđāļēāļāļģāļāļēāļāļāļąāļāļāļāļēāļāļēāļĢ .
Skills:
Compliance, Data Analysis, Power BI
Job type:
Full-time
Salary:
negotiable
- Build and maintain an HR data repository tailored to the food business under ThaiBev group, focusing on metrics critical to food operations, such as labor productivity, turnover by location, and shift coverage efficiency.
- Ensure data integrity and compliance with industry-specific labor regulations, maintaining a transparent and accurate source of HR information.
- Collaborate with operations teams to integrate labor data from multiple food business units, enabling holistic insights across various branches and regions.
- Assist HR Line Manager on Strategic HR Analytics for Workforce OptimizationConduct data analysis on staffing patterns, turnover rates, and workforce efficiency to identify optimization opportunities aligned with food business cycles.
- Use predictive analytics to anticipate workforce needs for peak and off-peak seasons, aiding in proactive staffing and cost control with operation team to centralization.
- Assist on Commercial Structure and Labor Cost Management for Food OperationsAnalyze labor costs relative to revenue and operational efficiency within different food outlets, providing insights to optimize staffing while maximizing profitability.
- Support the development of labor cost budgets that align with product pricing and sales targets in the food sector, helping maintain competitive yet profitable operations.
- Generate regular reports on labor cost performance against targets, identifying areas for improvement and enabling business leaders to adjust strategy as needed.
- Be Leader on developing Power BI Development for Real-Time Food Business InsightsDesign and deploy Power BI dashboards specific to food operations, offering real-time insights on key metrics like labor costs, staffing levels, and turnover rates across outlets.
- Collaborate with senior leaders in the food division to customize dashboards, highlighting KPIs that impact food production, service speed, and customer satisfaction.
- Continuously update Power BI capabilities to provide comprehensive, up-to-date views on HR metrics essential to food business strategy.
- 3+ years of experience in analytics, data management not specific in HR experience.
- Demonstrated proficiency in Power BI development and advanced Excel skills, including VBA, macros, and pivot tables.
- Prior experience in labor cost analysis, commercial structure evaluation.
- Contact Information:-.
- Oishi Group Public Company Limited.
- CW Tower, No.90. Ratchadapisek Road, Huai Khwang, Bangkok.
Experience:
2 years required
Skills:
Research, Python, SQL
Job type:
Full-time
Salary:
negotiable
- Develop machine learning models such as credit model, income estimation model and fraud model.
- Research on cutting-edge technology to enhance existing model performance.
- Explore and conduct feature engineering on existing data set (telco data, retail store data, loan approval data).
- Develop sentimental analysis model in order to support collection strategy.
- Bachelor Degree in Computer Science, Operations Research, Engineering, or related quantitative discipline.
- 2-5 years of experiences in programming languages such as Python, SQL or Scala.
- 5+ years of hands-on experience in building & implementing AI/ML solutions for senior role.
- Experience with python libraries - Numpy, scikit-learn, OpenCV, Tensorflow, Pytorch, Flask, Django.
- Experience with source version control (Git, Bitbucket).
- Proven knowledge on Rest API, Docker, Google Big Query, VScode.
- Strong analytical skills and data-driven thinking.
- Strong understanding of quantitative analysis methods in relation to financial institutions.
- Ability to clearly communicate modeling results to a wide range of audiences.
- Nice to have.
- Experience in image processing or natural language processing (NLP).
- Solid understanding in collection model.
- Familiar with MLOps concepts.
Skills:
Industry trends, Statistics, Python
Job type:
Full-time
Salary:
negotiable
- Develop and execute a forward-thinking analytics strategy tailored to the retail industry, focusing on leveraging data platforms to drive revenue growth, operational efficiency, and customer satisfaction.
- Lead, mentor, and inspire a team of data scientists and analysts, fostering a culture of innovation, collaboration, and data-driven decision-making.
- Stay ahead of industry trends, emerging technologies, and best practices in data science and retail analytics to maintain CP Axtra s competitive edge.
- Analytics Execution.
- Oversee the integration of diverse data sources, including POS systems, CRM platforms, online transactions, and third-party providers, into our cloud-based data platform.
- Design and develop advanced machine learning models, algorithms, and statistical analyses to uncover actionable insights related to customer behavior, product performance, and market trends.
- Apply expertise in recommendation and personalization algorithms to enhance customer experiences and engagement.
- Deliver data-driven solutions to optimize pricing strategies, inventory management, and promotional campaigns, leveraging state-of-the-art analytics tools and methodologies.
- Business Partnership.
- Partner closely with retail operations, marketing, and sales teams to understand business challenges and provide tailored analytical support that aligns with strategic objectives.
- Identify opportunities to enhance customer segmentation, personalized marketing efforts, and customer retention strategies through advanced data science techniques.
- Act as a key advisor to senior leadership, translating complex data insights into actionable recommendations and business value.
- Performance Monitoring and Optimization.
- Define and monitor key performance indicators (KPIs) related to retail operations, such as sales conversion rates, customer lifetime value, and basket analysis.
- Leverage analytics to continuously assess and optimize business processes, driving operational efficiency and profitability.
- Communication and Presentation.
- Present complex analytical findings, models, and recommendations to stakeholders in a clear, impactful, and visually compelling manner.
- Collaborate across departments to implement data-driven initiatives that align with CPaxtra s goals and drive tangible outcomes.
- Education and Experience.
- Bachelor s degree in Statistics, Mathematics, Computer Science, Data Science, Economics, or a related field (Master s or PhD strongly preferred).
- Extensive experience in analytics, data science, or business intelligence roles, with significant exposure to the retail industry.
- Technical Skills.
- Advanced proficiency in Python, R, SQL, and machine learning frameworks.
- Expertise in data visualization tools (e.g., Tableau, Power BI) and cloud-based data platforms (e.g., AWS, GCP, Azure).
- In-depth knowledge of big data technologies (e.g., Spark, Hadoop) and modern data engineering practices.
- Strong understanding of recommendation/personalization algorithms and data processing technologies.
- Leadership and Business Acumen.
- Proven ability to lead high-performing teams in a dynamic, fast-paced environment.
- Exceptional strategic thinking and problem-solving skills with a demonstrated focus on delivering business value.
- Deep understanding of retail operations, including inventory management, customer journey mapping, and merchandising strategies.
- CP AXTRA | Lotus's
- CP AXTRA Public Company Limited.
- Nawamin Office: Buengkum, Bangkok 10230, Thailand.
- By applying for this position, you consent to the collection, use and disclosure of your personal data to us, our recruitment firms and all relevant third parties for the purpose of processing your application for this job position (or any other suitable positions within Lotus's and its subsidiaries, if any). You understand and acknowledge that your personal data will be processed in accordance with the law and our policy. .
Experience:
1 year required
Skills:
Statistics, Data Analysis, Finance
Job type:
Full-time
Salary:
negotiable
- Bachelor s degree in Statistics, Economics, Mathematics, or related field.
- 1-3 years of experience in data analysis or related roles. Experience in banking or finance preferred.
- Proficiency in Excel, SQL, Python/R, data visualization tools like Tableau or Power BI. Strong statistical analysis skills.
- Strong understanding of data analysis, statistical methods, and business insights. Knowledge of user personas and journey mapping in data-centric roles.
- Contact: [email protected] (K.Thipwimon).
- āļāđāļēāļāļŠāļēāļĄāļēāļĢāļāļāđāļēāļāđāļĨāļ°āļĻāļķāļāļĐāļēāļāđāļĒāļāļēāļĒāļāļ§āļēāļĄāđāļāđāļāļŠāđāļ§āļāļāļąāļ§āļāļāļāļāļāļēāļāļēāļĢāļāļĢāļļāļāđāļāļĒ āļāļģāļāļąāļ (āļĄāļŦāļēāļāļ) āļāļĩāđ https://krungthai.com/th/content/privacy-policy āļāļąāđāļāļāļĩāđ āļāļāļēāļāļēāļĢāđāļĄāđāļĄāļĩāđāļāļāļāļēāļŦāļĢāļ·āļāļāļ§āļēāļĄāļāļģāđāļāđāļāđāļāđ āļāļĩāđāļāļ°āļāļĢāļ°āļĄāļ§āļĨāļāļĨāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļāđāļāļāđāļŦāļ§ āļĢāļ§āļĄāļāļķāļāļāđāļāļĄāļđāļĨāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļāļĻāļēāļŠāļāļēāđāļĨāļ°/āļŦāļĢāļ·āļāļŦāļĄāļđāđāđāļĨāļŦāļīāļ āļāļķāđāļāļāļēāļāļāļĢāļēāļāļāļāļĒāļđāđāđāļāļŠāļģāđāļāļēāļāļąāļāļĢāļāļĢāļ°āļāļģāļāļąāļ§āļāļĢāļ°āļāļēāļāļāļāļāļāļāđāļēāļāđāļāđāļāļĒāđāļēāļāđāļ āļāļąāļāļāļąāđāļ āļāļĢāļļāļāļēāļāļĒāđāļēāļāļąāļāđāļŦāļĨāļāđāļāļāļŠāļēāļĢāđāļāđ āļĢāļ§āļĄāļāļķāļāļŠāļģāđāļāļēāļāļąāļāļĢāļāļĢāļ°āļāļģāļāļąāļ§āļāļĢāļ°āļāļēāļāļ āļŦāļĢāļ·āļāļāļĢāļāļāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļāđāļāļāđāļŦāļ§āļŦāļĢāļ·āļāļāđāļāļĄāļđāļĨāļāļ·āđāļāđāļ āļāļķāđāļāđāļĄāđāđāļāļĩāđāļĒāļ§āļāđāļāļāļŦāļĢāļ·āļāđāļĄāđāļāļģāđāļāđāļāļŠāļģāļŦāļĢāļąāļāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāđāļāļāļēāļĢāļŠāļĄāļąāļāļĢāļāļēāļāđāļ§āđāļāļāđāļ§āđāļāđāļāļāđ āļāļāļāļāļēāļāļāļĩāđ āļāļĢāļļāļāļēāļāļģāđāļāļīāļāļāļēāļĢāđāļŦāđāđāļāđāđāļāļ§āđāļēāđāļāđāļāļģāđāļāļīāļāļāļēāļĢāļĨāļāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļāđāļāļāđāļŦāļ§ (āļāđāļēāļĄāļĩ) āļāļāļāļāļēāļāđāļĢāļāļđāđāļĄāđāđāļĨāļ°āđāļāļāļŠāļēāļĢāļāļ·āđāļāđāļāļāđāļāļāļāļĩāđāļāļ°āļāļąāļāđāļŦāļĨāļāđāļāļāļŠāļēāļĢāļāļąāļāļāļĨāđāļēāļ§āđāļ§āđāļāļāđāļ§āđāļāđāļāļāđāđāļĨāđāļ§āļāđāļ§āļĒ āļāļąāđāļāļāļĩāđ āļāļāļēāļāļēāļĢāļĄāļĩāļāļ§āļēāļĄāļāļģāđāļāđāļāļāđāļāļāđāļāđāļāļĢāļ§āļāļĢāļ§āļĄāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄāļāļāļāļāđāļēāļāđāļāļ·āđāļāļāļĢāļĢāļĨāļļāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāđāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāļĢāļąāļāļāļļāļāļāļĨāđāļāđāļēāļāļģāļāļēāļ āļŦāļĢāļ·āļāļāļēāļĢāļāļĢāļ§āļāļŠāļāļāļāļļāļāļŠāļĄāļāļąāļāļī āļĨāļąāļāļĐāļāļ°āļāđāļāļāļŦāđāļēāļĄ āļŦāļĢāļ·āļāļāļīāļāļēāļĢāļāļēāļāļ§āļēāļĄāđāļŦāļĄāļēāļ°āļŠāļĄāļāļāļāļāļļāļāļāļĨāļāļĩāđāļāļ°āđāļŦāđāļāļģāļĢāļāļāļģāđāļŦāļāđāļ āļāļķāđāļāļāļēāļĢāđāļŦāđāļāļ§āļēāļĄāļĒāļīāļāļĒāļāļĄāđāļāļ·āđāļāđāļāđāļāļĢāļ§āļāļĢāļ§āļĄ āđāļāđ āļŦāļĢāļ·āļāđāļāļīāļāđāļāļĒāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄāļāļāļāļāđāļēāļāļĄāļĩāļāļ§āļēāļĄāļāļģāđāļāđāļāļŠāļģāļŦāļĢāļąāļāļāļēāļĢāđāļāđāļēāļāļģāļŠāļąāļāļāļēāđāļĨāļ°āļāļēāļĢāđāļāđāļĢāļąāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāļāļēāļĄāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāļāļąāļāļāļĨāđāļēāļ§āļāđāļēāļāļāđāļ āđāļāļāļĢāļāļĩāļāļĩāđāļāđāļēāļāđāļĄāđāđāļŦāđāļāļ§āļēāļĄāļĒāļīāļāļĒāļāļĄāđāļāļāļēāļĢāđāļāđāļāļĢāļ§āļāļĢāļ§āļĄ āđāļāđ āļŦāļĢāļ·āļāđāļāļīāļāđāļāļĒāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄ āļŦāļĢāļ·āļāļĄāļĩāļāļēāļĢāļāļāļāļāļ§āļēāļĄāļĒāļīāļāļĒāļāļĄāđāļāļ āļēāļĒāļŦāļĨāļąāļ āļāļāļēāļāļēāļĢāļāļēāļāđāļĄāđāļŠāļēāļĄāļēāļĢāļāļāļģāđāļāļīāļāļāļēāļĢāđāļāļ·āđāļāļāļĢāļĢāļĨāļļāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāļāļąāļāļāļĨāđāļēāļ§āļāđāļēāļāļāđāļāđāļāđ āđāļĨāļ°āļāļēāļ āļāļģāđāļŦāđāļāđāļēāļāļŠāļđāļāđāļŠāļĩāļĒāđāļāļāļēāļŠāđāļāļāļēāļĢāđāļāđāļĢāļąāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāļĢāļąāļāđāļāđāļēāļāļģāļāļēāļāļāļąāļāļāļāļēāļāļēāļĢ .
Skills:
Project Management, Scrum, Product Owner
Job type:
Full-time
Salary:
negotiable
- Bachelor s degree in Business Administration, Innovation Management, Computer Science, Data Science, or a related field.
- At least 7 years of experience managing projects, with at least 2 years focused on innovation, digital transformation, or emerging technologies.
- Proven experience in end-to-end project management, including planning, execution, monitoring, and delivery.
- Experience working with project management tools such as JIRA, Trello, Asana, or MS Project.
- Knowledge of data analytics frameworks, predictive models, and data-driven decision-making methodologies.
- Understanding of emerging technologies (e.g., AI, machine learning, Generative AI, IoT) and innovation frameworks.
- Strong analytical, problem-solving, and decision-making skills.
- Excellent stakeholder management, communication, and presentation skills.
- Ability to work in a fast-paced, agile environment with cross-functional teams.
- Certifications: PMP, Prince2, Agile (Scrum Master, Product Owner), or Design Thinking certifications.
- Contact:.
- āļāđāļēāļāļŠāļēāļĄāļēāļĢāļāļāđāļēāļāđāļĨāļ°āļĻāļķāļāļĐāļēāļāđāļĒāļāļēāļĒāļāļ§āļēāļĄāđāļāđāļāļŠāđāļ§āļāļāļąāļ§āļāļāļāļāļāļēāļāļēāļĢāļāļĢāļļāļāđāļāļĒ āļāļģāļāļąāļ (āļĄāļŦāļēāļāļ) āļāļĩāđ https://krungthai.com/th/content/privacy-policy āļāļąāđāļāļāļĩāđ āļāļāļēāļāļēāļĢāđāļĄāđāļĄāļĩāđāļāļāļāļēāļŦāļĢāļ·āļāļāļ§āļēāļĄāļāļģāđāļāđāļāđāļāđ āļāļĩāđāļāļ°āļāļĢāļ°āļĄāļ§āļĨāļāļĨāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļāđāļāļāđāļŦāļ§ āļĢāļ§āļĄāļāļķāļāļāđāļāļĄāļđāļĨāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļāļĻāļēāļŠāļāļēāđāļĨāļ°/āļŦāļĢāļ·āļāļŦāļĄāļđāđāđāļĨāļŦāļīāļ āļāļķāđāļāļāļēāļāļāļĢāļēāļāļāļāļĒāļđāđāđāļāļŠāļģāđāļāļēāļāļąāļāļĢāļāļĢāļ°āļāļģāļāļąāļ§āļāļĢāļ°āļāļēāļāļāļāļāļāļāđāļēāļāđāļāđāļāļĒāđāļēāļāđāļ āļāļąāļāļāļąāđāļ āļāļĢāļļāļāļēāļāļĒāđāļēāļāļąāļāđāļŦāļĨāļāđāļāļāļŠāļēāļĢāđāļāđ āļĢāļ§āļĄāļāļķāļāļŠāļģāđāļāļēāļāļąāļāļĢāļāļĢāļ°āļāļģāļāļąāļ§āļāļĢāļ°āļāļēāļāļ āļŦāļĢāļ·āļāļāļĢāļāļāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļāđāļāļāđāļŦāļ§āļŦāļĢāļ·āļāļāđāļāļĄāļđāļĨāļāļ·āđāļāđāļ āļāļķāđāļāđāļĄāđāđāļāļĩāđāļĒāļ§āļāđāļāļāļŦāļĢāļ·āļāđāļĄāđāļāļģāđāļāđāļāļŠāļģāļŦāļĢāļąāļāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāđāļāļāļēāļĢāļŠāļĄāļąāļāļĢāļāļēāļāđāļ§āđāļāļāđāļ§āđāļāđāļāļāđ āļāļāļāļāļēāļāļāļĩāđ āļāļĢāļļāļāļēāļāļģāđāļāļīāļāļāļēāļĢāđāļŦāđāđāļāđāđāļāļ§āđāļēāđāļāđāļāļģāđāļāļīāļāļāļēāļĢāļĨāļāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļāđāļāļāđāļŦāļ§ (āļāđāļēāļĄāļĩ) āļāļāļāļāļēāļāđāļĢāļāļđāđāļĄāđāđāļĨāļ°āđāļāļāļŠāļēāļĢāļāļ·āđāļāđāļāļāđāļāļāļāļĩāđāļāļ°āļāļąāļāđāļŦāļĨāļāđāļāļāļŠāļēāļĢāļāļąāļāļāļĨāđāļēāļ§āđāļ§āđāļāļāđāļ§āđāļāđāļāļāđāđāļĨāđāļ§āļāđāļ§āļĒ āļāļąāđāļāļāļĩāđ āļāļāļēāļāļēāļĢāļĄāļĩāļāļ§āļēāļĄāļāļģāđāļāđāļāļāđāļāļāđāļāđāļāļĢāļ§āļāļĢāļ§āļĄāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄāļāļāļāļāđāļēāļāđāļāļ·āđāļāļāļĢāļĢāļĨāļļāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāđāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāļĢāļąāļāļāļļāļāļāļĨāđāļāđāļēāļāļģāļāļēāļ āļŦāļĢāļ·āļāļāļēāļĢāļāļĢāļ§āļāļŠāļāļāļāļļāļāļŠāļĄāļāļąāļāļī āļĨāļąāļāļĐāļāļ°āļāđāļāļāļŦāđāļēāļĄ āļŦāļĢāļ·āļāļāļīāļāļēāļĢāļāļēāļāļ§āļēāļĄāđāļŦāļĄāļēāļ°āļŠāļĄāļāļāļāļāļļāļāļāļĨāļāļĩāđāļāļ°āđāļŦāđāļāļģāļĢāļāļāļģāđāļŦāļāđāļ āļāļķāđāļāļāļēāļĢāđāļŦāđāļāļ§āļēāļĄāļĒāļīāļāļĒāļāļĄāđāļāļ·āđāļāđāļāđāļāļĢāļ§āļāļĢāļ§āļĄ āđāļāđ āļŦāļĢāļ·āļāđāļāļīāļāđāļāļĒāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄāļāļāļāļāđāļēāļāļĄāļĩāļāļ§āļēāļĄāļāļģāđāļāđāļāļŠāļģāļŦāļĢāļąāļāļāļēāļĢāđāļāđāļēāļāļģāļŠāļąāļāļāļēāđāļĨāļ°āļāļēāļĢāđāļāđāļĢāļąāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāļāļēāļĄāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāļāļąāļāļāļĨāđāļēāļ§āļāđāļēāļāļāđāļ āđāļāļāļĢāļāļĩāļāļĩāđāļāđāļēāļāđāļĄāđāđāļŦāđāļāļ§āļēāļĄāļĒāļīāļāļĒāļāļĄāđāļāļāļēāļĢāđāļāđāļāļĢāļ§āļāļĢāļ§āļĄ āđāļāđ āļŦāļĢāļ·āļāđāļāļīāļāđāļāļĒāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄ āļŦāļĢāļ·āļāļĄāļĩāļāļēāļĢāļāļāļāļāļ§āļēāļĄāļĒāļīāļāļĒāļāļĄāđāļāļ āļēāļĒāļŦāļĨāļąāļ āļāļāļēāļāļēāļĢāļāļēāļāđāļĄāđāļŠāļēāļĄāļēāļĢāļāļāļģāđāļāļīāļāļāļēāļĢāđāļāļ·āđāļāļāļĢāļĢāļĨāļļāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāļāļąāļāļāļĨāđāļēāļ§āļāđāļēāļāļāđāļāđāļāđ āđāļĨāļ°āļāļēāļ āļāļģāđāļŦāđāļāđāļēāļāļŠāļđāļāđāļŠāļĩāļĒāđāļāļāļēāļŠāđāļāļāļēāļĢāđāļāđāļĢāļąāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāļĢāļąāļāđāļāđāļēāļāļģāļāļēāļāļāļąāļāļāļāļēāļāļēāļĢ .
Experience:
No experience required
Skills:
Electrical Engineering, Mechanical Engineering, English
Job type:
Full-time
- Serve as the main contact for network investigations.
- Monitor GSA internal networks and data hall environments.
- Interpret and address connectivity alerts.
- Lead incident management events and create event tickets.
- Perform configuration tasks and adhere to security policies.
- Research and summarize events, providing reports.
- Coordinate with carriers to resolve customer issues.
- Provide input for network management optimization.
- Troubleshoot and escalate issues as needed.
- Deliver timely and accurate end-to-end support.
- Document actions and provide peer coaching/training.
- Job Qualifications.
- Bachelor's degree in information technology, computer science or related field.
- Flexible schedule availability, including nights, weekends, and shift rotations.
- Strong focus on customer service solutions.
- Understanding of various network topologies.
- Excellent communication skills via direct contact, phone, email, and documentation/tracking incidents.
- Knowledge of OSI Model and troubleshooting techniques.
- Familiarity with industry cabling standards and datacenter infrastructure.
- Proficiency in interacting with computing systems.
- Ability to navigate and utilize ticketing systems effectively.
- Comfortable working in a fast-paced environment with professionalism and flexibility.
- Punctual, reliable, and able to manage deadlines effectively.
- Strong organizational skills.
- Familiar with Computer literate with an emphasis on Microsoft Office Suite.
- Experience with equipment terminal access applications (Ex.: CRT, Putty, SSH).
- Experience with network monitoring software applications.
- We welcome recent graduates and those starting out in their careers to apply for this engineer-level position.
- Leader position is reserved for candidates with direct experience only.
- Creativity, problem solving skills, negotiation and systematic thinking.
- Fluent in English both written and verbal (Minimum 500 TOEIC score).
- Goal-Oriented, Unity, Learning, Flexible.
Experience:
3 years required
Skills:
Microsoft Azure, SQL, UNIX, Python, Hadoop
Job type:
Full-time
Salary:
negotiable
- Develop data pipeline automation using Azure technologies, Databricks and Data Factory.
- Understand data, reports and dashboards requirements, develop data visualization using Power BI, Tableau by working across workstreams to support data requirements including reports and dashboards and collaborate with data scientists, data analyst, data governance team or business stakeholders on several projects.
- Analyze and perform data profiling to understand data patterns following Data Qualit ...
- 3 years+ experience in big data technology, data engineering, data analytic application system development.
- Have an experience of unstructured data for business Intelligence or computer science would be advantage.
- Technical skill in SQL, UNIX and Shell Script, Python, R Programming, Spark, Hadoop programming.
Skills:
SQL, Oracle, Data Warehousing
Job type:
Full-time
Salary:
negotiable
- Bachelor s degree in Computer Science, Information Systems, Engineering, or a related field.
- At least 7 years of experience as a Data Engineer or in a related role.
- Hands-on experience with SQL, database management (e.g., Oracle, SQL Server, PostgreSQL), and data warehousing concepts.
- Experience with ETL/ELT tools such as Talend, Apache NiFi, or similar.
- Proficiency in programming languages like Python, Java, or Scala for data manipulation and automation.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Knowledge of big data technologies such as Hadoop, Spark, or Kafka.
- Strong understanding of data governance, security, and privacy frameworks in a financial services context.
- Excellent problem-solving skills and attention to detail.
- Experience working with Data Visualization or BI tools like Power BI, Tableau.
- Familiarity with machine learning concepts, model deployment, and AI applications.
- Banking or financial services industry experience, especially in retail or wholesale banking data solutions.
- Certification in cloud platforms (e.g., AWS Certified Data Engineer, Microsoft Azure Data Engineer, Google Professional Data Engineer)..
- Contact:.
- āļāđāļēāļāļŠāļēāļĄāļēāļĢāļāļāđāļēāļāđāļĨāļ°āļĻāļķāļāļĐāļēāļāđāļĒāļāļēāļĒāļāļ§āļēāļĄāđāļāđāļāļŠāđāļ§āļāļāļąāļ§āļāļāļāļāļāļēāļāļēāļĢāļāļĢāļļāļāđāļāļĒ āļāļģāļāļąāļ (āļĄāļŦāļēāļāļ) āļāļĩāđ https://krungthai.com/th/content/privacy-policy āļāļąāđāļāļāļĩāđ āļāļāļēāļāļēāļĢāđāļĄāđāļĄāļĩāđāļāļāļāļēāļŦāļĢāļ·āļāļāļ§āļēāļĄāļāļģāđāļāđāļāđāļāđ āļāļĩāđāļāļ°āļāļĢāļ°āļĄāļ§āļĨāļāļĨāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļāđāļāļāđāļŦāļ§ āļĢāļ§āļĄāļāļķāļāļāđāļāļĄāļđāļĨāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļāļĻāļēāļŠāļāļēāđāļĨāļ°/āļŦāļĢāļ·āļāļŦāļĄāļđāđāđāļĨāļŦāļīāļ āļāļķāđāļāļāļēāļāļāļĢāļēāļāļāļāļĒāļđāđāđāļāļŠāļģāđāļāļēāļāļąāļāļĢāļāļĢāļ°āļāļģāļāļąāļ§āļāļĢāļ°āļāļēāļāļāļāļāļāļāđāļēāļāđāļāđāļāļĒāđāļēāļāđāļ āļāļąāļāļāļąāđāļ āļāļĢāļļāļāļēāļāļĒāđāļēāļāļąāļāđāļŦāļĨāļāđāļāļāļŠāļēāļĢāđāļāđ āļĢāļ§āļĄāļāļķāļāļŠāļģāđāļāļēāļāļąāļāļĢāļāļĢāļ°āļāļģāļāļąāļ§āļāļĢāļ°āļāļēāļāļ āļŦāļĢāļ·āļāļāļĢāļāļāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļāđāļāļāđāļŦāļ§āļŦāļĢāļ·āļāļāđāļāļĄāļđāļĨāļāļ·āđāļāđāļ āļāļķāđāļāđāļĄāđāđāļāļĩāđāļĒāļ§āļāđāļāļāļŦāļĢāļ·āļāđāļĄāđāļāļģāđāļāđāļāļŠāļģāļŦāļĢāļąāļāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāđāļāļāļēāļĢāļŠāļĄāļąāļāļĢāļāļēāļāđāļ§āđāļāļāđāļ§āđāļāđāļāļāđ āļāļāļāļāļēāļāļāļĩāđ āļāļĢāļļāļāļēāļāļģāđāļāļīāļāļāļēāļĢāđāļŦāđāđāļāđāđāļāļ§āđāļēāđāļāđāļāļģāđāļāļīāļāļāļēāļĢāļĨāļāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļāđāļāļāđāļŦāļ§ (āļāđāļēāļĄāļĩ) āļāļāļāļāļēāļāđāļĢāļāļđāđāļĄāđāđāļĨāļ°āđāļāļāļŠāļēāļĢāļāļ·āđāļāđāļāļāđāļāļāļāļĩāđāļāļ°āļāļąāļāđāļŦāļĨāļāđāļāļāļŠāļēāļĢāļāļąāļāļāļĨāđāļēāļ§āđāļ§āđāļāļāđāļ§āđāļāđāļāļāđāđāļĨāđāļ§āļāđāļ§āļĒ āļāļąāđāļāļāļĩāđ āļāļāļēāļāļēāļĢāļĄāļĩāļāļ§āļēāļĄāļāļģāđāļāđāļāļāđāļāļāđāļāđāļāļĢāļ§āļāļĢāļ§āļĄāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄāļāļāļāļāđāļēāļāđāļāļ·āđāļāļāļĢāļĢāļĨāļļāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāđāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāļĢāļąāļāļāļļāļāļāļĨāđāļāđāļēāļāļģāļāļēāļ āļŦāļĢāļ·āļāļāļēāļĢāļāļĢāļ§āļāļŠāļāļāļāļļāļāļŠāļĄāļāļąāļāļī āļĨāļąāļāļĐāļāļ°āļāđāļāļāļŦāđāļēāļĄ āļŦāļĢāļ·āļāļāļīāļāļēāļĢāļāļēāļāļ§āļēāļĄāđāļŦāļĄāļēāļ°āļŠāļĄāļāļāļāļāļļāļāļāļĨāļāļĩāđāļāļ°āđāļŦāđāļāļģāļĢāļāļāļģāđāļŦāļāđāļ āļāļķāđāļāļāļēāļĢāđāļŦāđāļāļ§āļēāļĄāļĒāļīāļāļĒāļāļĄāđāļāļ·āđāļāđāļāđāļāļĢāļ§āļāļĢāļ§āļĄ āđāļāđ āļŦāļĢāļ·āļāđāļāļīāļāđāļāļĒāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄāļāļāļāļāđāļēāļāļĄāļĩāļāļ§āļēāļĄāļāļģāđāļāđāļāļŠāļģāļŦāļĢāļąāļāļāļēāļĢāđāļāđāļēāļāļģāļŠāļąāļāļāļēāđāļĨāļ°āļāļēāļĢāđāļāđāļĢāļąāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāļāļēāļĄāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāļāļąāļāļāļĨāđāļēāļ§āļāđāļēāļāļāđāļ āđāļāļāļĢāļāļĩāļāļĩāđāļāđāļēāļāđāļĄāđāđāļŦāđāļāļ§āļēāļĄāļĒāļīāļāļĒāļāļĄāđāļāļāļēāļĢāđāļāđāļāļĢāļ§āļāļĢāļ§āļĄ āđāļāđ āļŦāļĢāļ·āļāđāļāļīāļāđāļāļĒāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄ āļŦāļĢāļ·āļāļĄāļĩāļāļēāļĢāļāļāļāļāļ§āļēāļĄāļĒāļīāļāļĒāļāļĄāđāļāļ āļēāļĒāļŦāļĨāļąāļ āļāļāļēāļāļēāļĢāļāļēāļāđāļĄāđāļŠāļēāļĄāļēāļĢāļāļāļģāđāļāļīāļāļāļēāļĢāđāļāļ·āđāļāļāļĢāļĢāļĨāļļāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāļāļąāļāļāļĨāđāļēāļ§āļāđāļēāļāļāđāļāđāļāđ āđāļĨāļ°āļāļēāļ āļāļģāđāļŦāđāļāđāļēāļāļŠāļđāļāđāļŠāļĩāļĒāđāļāļāļēāļŠāđāļāļāļēāļĢāđāļāđāļĢāļąāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāļĢāļąāļāđāļāđāļēāļāļģāļāļēāļāļāļąāļāļāļāļēāļāļēāļĢ .
Experience:
5 years required
Skills:
Statistics, Finance, Risk Management
Job type:
Full-time
Salary:
negotiable
- Bachelor s degree (or equivalent) degree in a quantitative field such as Data Science, Actuarial Science, Statistics, or Mathematics.
- 5+ years of related practical experience, preferably in commercial insurance sector.
- Solid understanding of insurance pricing principles, loss reserving, and risk assessment methodologies.
- Familiarity with insurance industry regulations, standards, and best practices.
- Develop and maintain loss cost models using GLMs and other advanced statistical techniques, incorporating relevant variables and factors for accurate pricing and risk assessment.
- Analyse historical insurance data to identify patterns and trends, and determine the impact of various factors on loss costs.
- Collaborate with underwriting, claims, and finance teams to understand business needs and provide data-driven insights for portfolio management.
- Conduct rate level reviews to ensure appropriate pricing of insurance products, considering risk exposure, market dynamics, and profitability goals.
- Enhance loss cost models over time by incorporating new data sources, refining variables,.
- and exploring innovative modelling techniques.
- Evaluate the impact of pricing strategies, policy changes, and market shifts on portfolio performance, and make recommendations for adjustments, if needed.
- Present findings and recommendations to stakeholders, including senior management and underwriting teams, in clear and concise reports.
- Work closely with other departments including Underwriting, Actuarial, and Risk Management, providing them with the data and insights needed to make evidence-based decisions.
- Functional Competency.
- Excellent analytical and problem-solving skills, with the ability to translate data into meaningful insights and recommendations.
- Strong communication skills to effectively convey complex findings and recommendations to both technical and non-technical stakeholders.
- Attention to detail and ability to work independently, managing multiple projects and deadlines efficiently.
- Strong proficiency in statistical modeling techniques, specifically GLMs, and experience with software tools like R, SAS, or Python.
- Proficiency with data analysis and visualisation tools and platforms, preferably Qliksense, Power BI, Alteryx, etc.
- Educational.
- Bachelor s degree (or equivalent) degree in a quantitative field such as Data Science, Actuarial Science, Statistics, or Mathematics.
- 5+ years of related practical experience, preferably in commercial insurance sector.
- Solid understanding of insurance pricing principles, loss reserving, and risk assessment methodologies.
- Familiarity with insurance industry regulations, standards, and best practices.
- Develop and maintain loss cost models using GLMs and other advanced statistical techniques, incorporating relevant variables and factors for accurate pricing and risk assessment.
- Analyse historical insurance data to identify patterns and trends, and determine the impact of various factors on loss costs.
- Collaborate with underwriting, claims, and finance teams to understand business needs and provide data-driven insights for portfolio management.
- Conduct rate level reviews to ensure appropriate pricing of insurance products, considering risk exposure, market dynamics, and profitability goals.
- Enhance loss cost models over time by incorporating new data sources, refining variables,.
- and exploring innovative modelling techniques.
- Evaluate the impact of pricing strategies, policy changes, and market shifts on portfolio performance, and make recommendations for adjustments, if needed.
- Present findings and recommendations to stakeholders, including senior management and underwriting teams, in clear and concise reports.
- Work closely with other departments including Underwriting, Actuarial, and Risk Management, providing them with the data and insights needed to make evidence-based decisions.
- Functional Competency.
- Excellent analytical and problem-solving skills, with the ability to translate data into meaningful insights and recommendations.
- Strong communication skills to effectively convey complex findings and recommendations to both technical and non-technical stakeholders.
- Attention to detail and ability to work independently, managing multiple projects and deadlines efficiently.
- Strong proficiency in statistical modeling techniques, specifically GLMs, and experience with software tools like R, SAS, or Python.
- Proficiency with data analysis and visualisation tools and platforms, preferably Qliksense, Power BI, Alteryx, etc.
Skills:
Assurance, Compliance
Job type:
Full-time
Salary:
negotiable
- Conduct detailed analysis of Enterprise Service revenue to identify trends in products and services within AIS Group.
- Verify the accuracy and completeness of revenue collection, promotion packages, and new services to ensure compliance with business conditions.
- Develop appropriate QA measures to minimize revenue loss and operational errors.
- Detect and investigate irregularities affecting revenue, such as real loss, opportunity loss, and fraud.
- Collaborate with relevant departments to address and rectify issues impacting revenue.
- Ensure the accuracy of service charges, promotion packages, and offerings for enterprise customers.
- Review and validate the calculation of postpaid voice, IDD, and IR services in the RBM system to prevent revenue loss.
- Utilize data analytics skills to analyze data from various sources, reflecting trends, performance, and efficiency of products and services.
- Prepare analysis reports to support management in strategy formulation and risk assessment.
Skills:
Big Data, Research, Statistics
Job type:
Full-time
Salary:
negotiable
- Design, code, experiment and implement models and algorithms to maximize customer experience, supply side value, business outcomes, and infrastructure readiness.
- Mine a big data of hundreds of millions of customers and more than 600M daily user generated events, supplier and pricing data, and discover actionable insights to drive improvements and innovation.
- Work with developers and a variety of business owners to deliver daily results with the best quality.
- Research discover and harness new ideas that can make a difference.
- What You'll Need to Succeed.
- 4+ years hands-on data science experience.
- Excellent understanding of AI/ML/DL and Statistics, as well as coding proficiency using related open source libraries and frameworks.
- Significant proficiency in SQL and languages like Python, PySpark and/or Scala.
- Can lead, work independently as well as play a key role in a team.
- Good communication and interpersonal skills for working in a multicultural work environment.
- It's Great if You Have.
- PhD or MSc in Computer Science / Operations Research / Statistics or other quantitative fields.
- Experience in NLP, image processing and/or recommendation systems.
- Hands on experience in data engineering, working with big data framework like Spark/Hadoop.
- Experience in data science for e-commerce and/or OTA.
- We welcome both local and international applications for this role. Full visa sponsorship and relocation assistance available for eligible candidates.
- Equal Opportunity Employer.
- At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person's merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics.
- We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our privacy policy.
- To all recruitment agencies: Agoda does not accept third party resumes. Please do not send resumes to our jobs alias, Agoda employees or any other organization location. Agoda is not responsible for any fees related to unsolicited resumes.
Experience:
No experience required
Skills:
Mechanical Engineering, Electrical Engineering, English
Job type:
Full-time
- Provide day to day installation, maintenance, and repair of all facilities in the data center.
- 24x7 shift work responsibility when qualified and designated.
- Provide requested reporting and documentation.
- Support of facility, development, and construction teams.
- Perform tasks as assigned by DC operation manager.
- Respond to customer requests, power, cooling, and facility audits.
- First tier investigate any power, communication, or cooling anomalies.
- Attend assigned meetings and training.
- Assist in ensuring customer compliance with GSA Acceptance Usage Policy (AUP).
- Provide technical escort when needed.
- Job Qualifications.
- Must be familiar with safety requirements and OSHA regulations or Thailand safety regulations.
- Basic understanding of electrical and mechanical systems that may be employed in a data center environment. This may include electrical feeders, transformers, generators, switchgear, UPS systems, DC power systems, ATS/STS units, PDU units, air handling units, cooling towers, and fire suppression systems.
- Familiar with Interpret wiring diagrams, schematics, and electrical drawings.
- Ability to express ideas clearly, concisely, and effectively with contractors performing maintenance or upgrades on systems installed in the data center environment.
- Excellent verbal, written, and interpersonal communication skills.
- Ability to analyze and make suggestions for problem resolution.
- Solve problems with good initiative and sound judgment.
- Creativity, problem solving skills, negotiation and systematic thinking.
- Fluent in English both written and verbal (Minimum 500 TOEIC score).
- Goal-Oriented, Unity, Learning, Flexible.
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