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āļāļąāļāļĐāļ°:
SQL, Research, Java
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Background in SQL, databases and/or data science OR.
- BS/MS in software engineering, computer science, mathematics.
- Document data sources in enterprise data catalog with metadata, lineage and classification information.
- Develop aggregations and algorithms needed for reporting and analytics with low level complexity.
- Implement minor changes to existing data visualization applications, reporting dashboards.
- Document modifications to reporting applications based on modifications applied.
- Comprehend and adhere to all data security policies and procedures.
- Create data tools for analytics and data scientist team members.
- Build analytical tools to provide actionable insights into key business KPIs, etc.
- Work with data engineers to optimize pipelines for scalability and data delivery.
- Functional Competency.
- Working knowledge with data and analytics framework supporting data lakes, warehouses, marts, reporting, etc.
- Experience with data tools for visualizations, analytics and reporting.
- Strong analytical skills with ability to research, assess and develop observations/findings.
- Ability to communicate findings, approaches to cross functional teams and stakeholders.
- 3+ years' hands-on experience with a data science background.
- Some programming skills in Java, Python and SQL.
- Clear hands-on experience with database systems - Cloud technologies (e.g. AWS, Azure, Google), in-memory database systems (e.g. HANA, Hazel cast, etc) and other database systems - traditional RDBMS (e.g. Teradata, SQL Server, Oracle), and NoSQL databases (e.g. Cassandra, MongoDB, DynamoDB).
- Educational.
- Background in SQL, databases and/or data science OR.
- BS/MS in software engineering, computer science, mathematics.
- Document data sources in enterprise data catalog with metadata, lineage and classification information.
- Develop aggregations and algorithms needed for reporting and analytics with low level complexity.
- Implement minor changes to existing data visualization applications, reporting dashboards.
- Document modifications to reporting applications based on modifications applied.
- Comprehend and adhere to all data security policies and procedures.
- Create data tools for analytics and data scientist team members.
- Build analytical tools to provide actionable insights into key business KPIs, etc.
- Work with data engineers to optimize pipelines for scalability and data delivery.
- Functional Competency.
- Working knowledge with data and analytics framework supporting data lakes, warehouses, marts, reporting, etc.
- Experience with data tools for visualizations, analytics and reporting.
- Strong analytical skills with ability to research, assess and develop observations/findings.
- Ability to communicate findings, approaches to cross functional teams and stakeholders.
- 3+ years' hands-on experience with a data science background.
- Some programming skills in Java, Python and SQL.
- Clear hands-on experience with database systems - Cloud technologies (e.g. AWS, Azure, Google), in-memory database systems (e.g. HANA, Hazel cast, etc) and other database systems - traditional RDBMS (e.g. Teradata, SQL Server, Oracle), and NoSQL databases (e.g. Cassandra, MongoDB, DynamoDB).
āļāļąāļāļĐāļ°:
Data Analysis, SQL, Excel, English
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Data Analysis: Conduct in-depth analysis of retail and wholesale business data to address specific business questions and challenges.
- Insight Generation: Interpret results from dashboards and data analyses to develop actionable insights and strategic recommendations.
- Requirement Gathering: Identify business problems, gather requirements, and propose potential solutions, including leveraging AI to enhance business operations.
- ML Model creations: Create data analytic model including both deterministic and machine learning model.
- AI vendors coordination's: Collaborate with external AI suppliers to align project objectives with technological capabilities.
- Cross-Departmental Collaboration: Work with various departments to develop and implement data-driven strategies that optimize business processes and decision-making.
- Communication: Act as a liaison between stakeholders and AI vendors, ensuring clear communication understanding of project requirements.
- Data analytics and AI Strategy Design; Design and recommend how Business Intelligence (BI) and AI technologies can address business problems and provide further insights.
- Decision making support: Present key findings from own analysis and strategic recommendations to business counterparts and senior management, focusing on project approaches and strategic planning.
- Bachelors' Degree or higher in Computer Science, Engineering, Information Technology, Management Information System.
- Strong business acumen, with a deep understanding of retail and wholesale business.
- At least 5 years of proven experience as a data analytic role (Retail or E-Commerce Business is preferable).
- Hands-on Experience in SQL, data cloud platform (e.g. Databricks, Snowflake, GCP, or AWS) and high proficiency in excel.
- Good knowledge of Statistics.
- Experience in Python (Pandas, Numpy, SparkSQL), Data Visualization (Tableau, Power BI) is a plus.
- Excellent communication skills with a ability to convey complex findings to non-technical stakeholders.
- Fluent in Thai and English.
- Having good attitude toward team working & willing to work hard.
āļāļąāļāļĐāļ°:
Finance, Compliance
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- 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.
āļāļąāļāļĐāļ°:
Data Analysis, Excel, Power BI
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Graduate with a Bachelor's/Master's Degree in Economics, Engineer, IT, or other related fields.
- Have an Experience in data analysis or performance reporting.
- Strong data analysis skills using Excel, Power BI, and SQL.
- Able to use VBA/Macro will be given special consideration.
- Experience in Retail businesses will be given special consideration..
- Tasks & responsibilities.
- Prepare and deliver daily, weekly, and monthly business reports to key stakeholders and business controllers.
- Recommend IT solutions for optimizing report generation across Financial, Commercial, and Operational areas.
- Ensure accuracy and consistency in data, readying it for comprehensive reporting.
- Provide data support to internal teams to meet reporting needs.
- Prepare additional ad hoc reports as assigned..
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- āļāļąāļāđāļāļĢāļĩāļĒāļĄāđāļāļāļŠāļēāļĢ daily briefing āđāļŦāđāļāļąāļāļāļĩāļĄ.
- āļāļķāļ redemption daily report āđāļāļ·āđāļāļāļĢāļ§āļāļŠāļāļāļāļ§āļēāļĄāļāļđāļāļāđāļāļ āđāļĨāļ°āļĢāļēāļĒāļāļēāļĢāļāđāļ Manager / Supervisor.
- āļāļąāļāļāļģāļĢāļēāļĒāļāļēāļāđāļāļŠāđāļĨāļ° feedback āļāđāļāđāļŠāļāļāđāļāļ°āļāđāļēāļāđ āļāļāļāļĨāļđāļāļāđāļē āđāļāđāļāļĢāļēāļĒāļāļēāļāļāļĢāļ°āļāļģāļ§āļąāļ / āļŠāļąāļāļāļēāļŦāđ / āđāļāļ·āļāļ / āđāļāļĢāļĄāļēāļŠ.
- āļāļēāļĢāļāļąāļāļāļģāļāļđāđāļĄāļ·āļ āđāļĨāļ° material āļāļāļāļāđāļēāļĒāļŊ.
- Support Daily Operation āļŦāļāđāļēāļāļēāļāļāļāļāļāđāļēāļĒāļĨāļđāļāļāđāļēāļŠāļąāļĄāļāļąāļāļāđ.
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- āļāļēāļĢāļāļĢāļ°āļŠāļēāļāļĢāļąāļ āđāļĨāļ° āļŠāđāļāļĄāļāļāļāļ·āļ Gift Card āļŠāļģāļŦāļĢāļąāļāļāļēāļĒ āđāļĨāļ° āļŠāļģāļŦāļĢāļąāļāđāļāļ āđāļŦāđāļāļąāļāļāļĩāļĄāđāļāļāđāļāļĩāļĒāļĢāđ.
- āļāļēāļĢāļāļĢāļ°āļŠāļēāļāļāļąāļāļŦāļāđāļ§āļĒāļāļēāļāļāļ·āđāļ.
āļāļąāļāļĐāļ°:
Data Analysis, SQL, Python
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Collaborate with business leaders to identify and prioritize data needs.
- Translate business goals into data requirements and actionable insights.
- Develop and maintain strong relationships with stakeholders across the organization.
- Lead the development and implementation of data strategies that align with business objectives.
- Ensure data governance policies and procedures are adhered to.
- Champion data quality, integrity, and security across the organization.
- Oversee the delivery of advanced analytics and business intelligence solutions.
- Provide strategic insights and recommendations based on data analysis.
- Utilize data to identify trends, opportunities, and potential risks.
- Mentor and guide data analysts and data scientists within the team.
- Drive continuous improvement in data processes and analytics capabilities.
- Manage and prioritize data projects to ensure timely delivery.
- Coordinate with IT and other departments to implement data solutions.
- Monitor and report on project progress and outcomes.
- Stay updated on the latest data technologies and methodologies.
- Ensure the use of best practices in data analytics and data science.
- Provide technical guidance and support to the team.
- Bachelor s degree in Data Science, Computer Science, Business Analytics, or a related field.
- Proven experience in a business partnering role, with the ability to influence and drive business strategy.
- Proficiency in data analysis tools and technologies (e.g., SQL, Python, Power BI).
- Strong project management abilities with experience in leading cross-functional projects.
- Has Finance and Accounting knowledge will be a plus.
- Strong ability to analyze user requirements, make recommendations and implement solution.
- Strategic thinker with a business-focused mindset.
- Strong oral and written communication skills.
- Strong communication and interpersonal skills, with the ability to explain complex data concepts to non-technical stakeholders.
- Ability to prioritize and execute in high-pressured environment.
- Ability to work in a fast-paced, dynamic environment.
- Strong problem-solving skills.
- 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. .
āļāļąāļāļĐāļ°:
Business Development, Software Development, Big Data
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- To build and maintain the information and forecasting system in order to support the company business development.
- To analyze data from various sources and system to develop dashboard for management.
- To identify, share and analyze market trends and changes.
- To develop Market Insight update platform for sharing with various departments of the organization.
- To provide business analysis data and benchmark of key principals to internal and external stakeholders.
- Help managing assigned projects in business development, customer management or any assign by supervise.
- Manage, monitor, and evaluate performance of subordinates to ensure achievement.
- Deliver updates to stakeholders based on analytics.
- Should have good experience in the application of standard software development principles.
- Should be able to work as an independent team member, capable of applying judgment to plan and execute tasks.
- Should also be able to coach, guide and mentor junior members in the team.
- Bachelor's Degree in Business Administration, Computer Science, Information Technology or related.
- Experience in working with big data, customer master data and business analytical tools.
- Experience with Qlik Sense or Power BI will be advantage.
- Analytical, strategic and result oriented with strong commercial sense.
- Independence and dynamic with decision making and problem solving skills.
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
5 āļāļĩāļāļķāđāļāđāļ
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļķāļāļāļēāļ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
Qualifications: Job requirements: Degree in Computer Science/IT or equivalent. Experience in data warehouse design. Relevant working with SQL as well as data integration & ETL tools. Experience with a variety of databases: Oracle, SQL Server, Spark, HBase, Hive etc. Experience with cloud platforms: GCP, AWS, Azure, etc. Working knowledge of software life cycles methodology either development and operation: DevOps, Agile, CI/CD, CMMI, ITIL, etc. Additional Qualifications for Big Data Engineer: Working knowledge of message queuing, stream processing, distributed data processing. Expe ...
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Analyze data and provide business insight.
- Assess risk and design mitigation actions based on data insight.
- Design dashboards / predictive models for decision-making management.
- Lead and Supervise team by projects.
āļāļąāļāļĐāļ°:
Data Analysis, English
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Data Innovation Team.
- āļāļāļīāļāļąāļāļīāļāļēāļāļĒāļąāļ āļāļĢāļīāļĐāļąāļ Infinitas by Krungthai
- As a data analyst in Infinitas, you would expect a new level of analytical experiences here. Being part of Data Innovation team, your goal is to make data useful for all stakeholders. Under the big umbrella of the leading bank in Thailand, Infinitas leverage the largest financial data sets from both traditional banking and mobile banking services. From customer digital footprint to branch, ATM and call center. We mea ...
- Job Responsibilities
- Conduct data inventory research with product owner, business owner and IT BA to gain full understandings of data availability.
- Communicate with business owners to translate business problem/challenge into actionable analytical solution
- Initiate EDA ideas to tag hidden opportunities for customer, product, channel and other various areas.
- Analyze digital and traditional user journey funnel and customer persona
- Visualize data for fast decision making and insight interpretation
- Define customer segmentations for strategy planning and marketing targeting
- Plan holistic A/B testing campaigns to evaluate data values on business impact
- Design and fulfill monitoring dashboards and automated reports
- English as working language
- Minimum of 3 years data analytics related working experiences
- At least 1 year of working experience directly communicate to business team
- Proficient in Python or SQL
- Advanced hands on experiences with visualization tool
- Strong communication and analytical thinking skills
- Good balance of data and business knowledge
- Fintech or banking industry
- Internet companies with mobile application.
- 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 .
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
3 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
Compliance, Legal, Risk Management
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Develop data security policy review, data security policy exceptions, and control risk mitigation processes.
- Define the security controls for access management lifecycle (i.e., requirement for creation, deletion, transfer and review).
- Operate:Advice on technology relating to Data Privacy and Protection (i.e., PDPA) related security controls implementation.
- Drive and support data security controls such as Data Loss Prevention (DLP), Data Masking, Data Encryption capabilities to protect sensitive data.
- Drive compliance (or collaborate with compliance team) to organization security policies, standards, metrics, and legal requirements.
- Communicate and enforce security policies, rules, and standards.
- Conduct impact assessment of data initiatives from a security point of view.
- Ensure the cryptographic keys and related components are safety and protection of confidential information.
- Resolve data security audit and risk findings.
- Review and develop security controls to current access controls policies and procedures.
- Provide requirements for create and manage roles, access rights (includes privileged access), authentication and identity within the environment.
- Conduct periodic review of user access.
- Review, approve and monitor the usage of privileged access.
- EDUCATION.
- Bachelor s degree in computer science, Information Systems, or equivalent education or work experience.
- EXPERIENCE.
- Work experience in privacy, compliance, information security, auditing or a related field may also be an accepted alternative, according to Cybersecurity.
- Minimum 3 years of experience in and strong knowledge of privacy, data, operational risk management, information security, or related areas in IT.
- OTHER REQUIREMENTS.
āļāļąāļāļĐāļ°:
Excel, Python, Power BI
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Create, Develop and Monitor Auto Replenishment & Parameter.
- Maintain and adjust parameters to optimize stock availability/ stock level during normal/month and promotion periods.
- Investigate and identify root cause of overstocking and OOS at Store/DC.
- Monitoring of target stock on normal/seasonal period to suit with business sale target.
- Adjust daily sales in system to correct average daily sales after promotion period.
- Forecasting demand in each promotion campaign to manage Parameter setting.
- Develop Daily KPI Dashboard to monitor sales performance VS Suggest number from system.
- Bachelor Degree of Supply Chain, Logistic, Economics, Mathematic and other relate filed.
- Have experience in Data analyst, Inventory Analyst, Inventory Planning at least 3-5 Years.
- Strong Mathematic skills is a must.
- Excellent for Excel (Pivot, VLOOKUP, VBA), Python, Power BI, Tableau.
- Have experience in Retail business /FMCG would be advantage.
- Good Analytic skills.
āļāļąāļāļĐāļ°:
Product Owner, Scrum, Project Management
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Collaborating with prospective users and clients to understand and anticipate their needs and translate them into product requirements.
- Defining the vision for the product team and maintaining a cohesive vision throughout the process.
- Creating a product road map based on this vision.
- Managing the product backlog and prioritizing the tasks based on changing requirements.
- Overseeing all stages of product creation, including design and development.
- Monitoring and evaluating product progress at each stage of the process.
- Working with the product team and end-users to deliver updates and status reports.
- Participating in Scrum meetings and product sprints.
- Bachelor degree.
- At least 4 years of working experience.
- At least 2 years of working experience in Project Management.
- In-depth knowledge of Scrum and Agile Software Development Methodology.
- Working knowledge of product development architecture.
- Proficiency in the use of analytic tools and strong analytical thinking.
- Ability to prioritize effectively.
- Contact Information:-.
- Office of Human Capital.
- THAI BEVERAGE PUBLIC COMPANY LIMITED.
- Lao Peng Nguan Building, Tower 1.
- 333 Vibhavadi Rangsit Road, Ladyao Subdistrict, Chatuchak District, Bangkok 10900.
āļāļąāļāļĐāļ°:
Big Data, ETL, SQL
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Develop and maintain robust data pipelines to ingest, process, and transform raw data into formats suitable for LLM training.
- Conduct meeting with users to understand the data requirements and perform database design based on data understanding and requirements with consideration for performance.
- Maintain data dictionary, relationship and its interpretation.
- Analyze problem and find resolution, as well as work closely with administrators to monitor performance and advise any necessary infrastructure changes.
- Work with business domain experts, data scientists and application developers to identify data that is relevant for analysis.
- Develop big data solutions for batch processing and near real-time streaming.
- Own end-to-end data ETL/ELT process framework from Data Source to Data warehouse.
- Select and integrate appropriate tools and frameworks required to provide requested capabilities.
- Design and develop BI solutions.
- Hands-on development mentality, with a willingness to troubleshoot and solve complex problems.
- Keep abreast of new developments in the big data ecosystem and learn new technologies.
- Ability to effectively work independently and handle multiple priorities.
- Bachelor degree or higher in Computer Science, Computer Engineering, Information Technology, Management Information System or an IT related field.
- 3+ year's experiences in Data Management or Data Engineer (Retail or E-Commerce business is preferrable).
- Expert experience in query language (SQL), Databrick SQL, PostgreSQL.
- Experience in Big Data Technologies like Hadoop, Apache Spark, Databrick.
- Experience in Python is a must.
- Experience in Generative AI is a must.
- Knowledge in machine/statistical learning, data mining is a plus.
- Strong analytical, problem solving, communication and interpersonal skills.
- Having good attitude toward team working and willing to work hard.
- 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. .
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
3 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
Data Analysis, SQL, Python, English, Thai
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Research on AI/ML, MarTech and AdTech to explore new tools and techniques.
- Prototype and test hyper-personalization engine using these innovations to ensure benefits and efficiency before full-scale deployment.
- Design, implement and automate personalization engine and recommendation system to enhance customer experiences and boost sales and marketing.
- Leverage Advanced analytics, AI/ML, and data mining techniques across various use cases to address business challenges.
- Design and conduct experiments, evaluate and maintain model to improve performance.
- Engage with key stakeholders, including IT, business, campaign and data teams to align on business requirements and integrate data solutions into our platforms.
- Participate in the vendor selection processes to identify and ensure the best external partners for data science and AI/ML projects.
- Bachelor s Degree or higher in Computer Science, Data Science, Engineering, Statistics, or any related field.
- Minimum of 3-5 years experience in data field and at least 2 years in data science, AI/ML engineer or a related field.
- Proficiency in some of the following: Recommendation engine, Reinforcement Learning, Python, PySpark and SQL and etc.
- Experience in building tools / models to support retention, up-cross selling, optimization, mobile app data and digital marketing is a plus.
- Ability to communicate and collaborate with cross-functional teams.
- Growth mindset and openness to continuously learning and facing new projects and new technologies.
- 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 .
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
2 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
Big Data, Good Communication Skills, Scala
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- You will be involved in all aspects of the project life cycle, including strategy, road-mapping, architecture, implementation and development.
- You will work with business and technical stakeholders to gather and analyse business requirements to convert them into the technical requirements, specifications, mapping documents.
- You will collaborate with technical teams, making sure the newly implemented solutions/technology are meeting business requirements.
- Outputs include workshop sessions and documentation including mapping documents.
- Develop solution proposals that provide details of project scope, approach, deliverables and project timeline.
- Skills and attributes for success.
- 2-4 years of experience in Big Data, data warehouse, data analytics projects, and/or any Information Management related projects.
- Prior experience building large scale enterprise data architectures using commercial and/or open source Data Analytics technologies.
- Ability to produce client ready solution, business understandable presentations and good communication skills to lead and run workshops.
- Strong knowledge of data manipulation languages such as Spark, Scala, Impala, Hive SQL, Apache Nifi and Kafka.
- Data modelling and architecting skills including strong foundation in data warehousing concepts, data normalisation, and dimensional data modelling such as OLAP, or data vault.
- Good knowledge in DevOps engineering using Continuous Integration/ Delivery tools.
- An in depth understanding of Cloud solutions (AWS, Azure and/or GCP) and experienced in integrating into traditional hosting/delivery models.
- Ideally, you ll also have.
- Experience in engaging with both technical and non-technical stakeholders.
- Strong consulting experience and background, including engaging directly with clients.
- Demonstrable Cloud experience with Azure, AWS or GCP.
- Configuration and management of databases.
- Experience with big data tools such as Hadoop, Spark, Kafka.
- Experience with AWS and MS cloud services.
- Python, SQL, Java, C++, Scala.
- Highly motivated individuals with excellent problem-solving skills and the ability to prioritize shifting workloads in a rapidly changing industry. An effective communicator, you ll be a confident leader equipped with strong people management skills and a genuine passion to make things happen in a dynamic organization.
- What working at EY offers.
- Support, coaching and feedback from some of the most engaging colleagues around.
- Opportunities to develop new skills and progress your career.
- The freedom and flexibility to handle your role in a way that s right for you.
- about EY
- As a global leader in assurance, tax, transaction and advisory services, we hire and develop the most passionate people in their field to help build a better working world. This starts with a culture that believes in giving you the training, opportunities and creative freedom to make things better. So that whenever you join, however long you stay, the exceptional EY experience lasts a lifetime.
- If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible.
- Join us in building a better working world. Apply now!.
āļāļąāļāļĐāļ°:
Excel, Meet Deadlines, Power BI
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Collect HR Data from a variety of data sources, including HRMS, Excel, Google Sheet and Text files.
- Preparing data and developing analytical reports in the HR area, such as HR Dashboard, to support executive decision-making.
- Analyzes and prepares Executive Dashboard in order to predict and find solutions with HR team member.
- Support the HR team by providing insightful information to support HR strategies.
- Bachelor s Degree in Business Administration or a related field.
- Minimum of 2 years of experience in an HR Data Analyst or HRIS role.
- Ability to manage multiple tasks/projects, work under pressure, and meet deadlines.
- Strong verbal and written communication skills, with excellent presentation abilities.
- Results-driven and solution-oriented.
- Experience with data visualization and analytics platforms such as Microsoft Power BI or Tableau.
- Proficiency in SQL, including platforms like PostgreSQL and Oracle DB.
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
3 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
Big Data, Hive, SAS
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- 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 .
āļāļąāļāļĐāļ°:
Business Development, Creative Thinking, Project Management, English
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Strong analytical and problem-solving skills to identify commercial opportunity.
- Working well in a cross-disciplinary team with different types of stakeholders (IT, Agency, Business, Management).
- Business Development of Data Intelligence for corporate strategy.
- Analyze internal and external data in various aspects to identify threats & opportunities and provide information/report for management or related business unit team to plan activities and strategies.
- Participate in the initiative's development plan of business unit / brand plans and align with corporate strategy, objectives and KPIs.
- Coordinate and consolidate with the related department to implement a project or tracking the project progress and provide corrective supervision if necessary.
- Create and deliver insights report on new ideas to the management team or business units and seek appropriate decisions, directions, and approvals.
- Bachelor s or Master s degree in business or related field of study.
- Minimum 5-8 years Performance Management function / Commercial Analyst roles.
- Experience in corporate/channel/brand/segment strategy.
- Experience working in Data Analytic related projects.
- Excellent analytical and problem-solving skills.
- Ability to apply logical and creative thinking to solve complex business problems.
- Ability to define the problems and frame answers in a logical and structured manner.
- Good project management, team leadership and sense of ownership.
- Good co-ordination skill with positive attitude and ability to work under pressure.
- Strong communications, customer relationship and negotiation skills.
- Good command of both written and spoken English.
- TECHNICAL SKILLS: Basic understanding of data ecosystem, Advanced skills in dashboard and BI tools.
- Conceptual knowledge of data and analytics, ETL, reporting tools, data governance, data warehousing, structured and unstructured data.
āļāļąāļāļĐāļ°:
ETL, Python
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- āļĢāļ§āļĄāļāđāļāļĄāļđāļĨāļāļīāļāļāļēāļāđāļŦāļĨāđāļāļāđāļāļĄāļđāļĨāļāđāļēāļāđ āļāļąāđāļāļ āļēāļĒāđāļĨāļ°āļ āļēāļĒāļāļāļ āđāļĨāļ°āļŠāļĢāđāļēāļāļāļąāļĨāļāļāļĢāļīāļāļķāļĄāđāļĨāļ°āļŠāļĢāđāļēāļāļāđāļāđāļāļ.
- āļāļēāļĢāļĢāļ§āļāļĢāļ§āļĄāļāđāļāļĄāļđāļĨāļāļĩāđāļĄāļĩāđāļāļĢāļāļŠāļĢāđāļēāļ (Structured Data) āđāļĨāļ°āđāļĄāđāļĄāļĩāđāļāļĢāļāļŠāļĢāđāļēāļ (Unstructured Data) āļāļĢāļ°āđāļĄāļīāļāļāļ§āļēāļĄāļāđāļāļāļāļēāļĢāđāļĨāļ°āļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāļāļēāļāļāļļāļĢāļāļīāļ.
- āļāļąāļāļĢāļ°āđāļāļĩāļĒāļāļāđāļāļĄāļđāļĨāļāļīāļ āļāļģāļāđāļāļĄāļđāļĨāļĄāļēāļāļģāļāļ§āļēāļĄāļŠāļ°āļāļēāļ (Data Cleansing + Shaping + ETL) āļĢāļ§āļĄāļāļķāļāļāļąāļāđāļāļĢāļĩāļĒāļĄāļāđāļāļĄāļđāļĨāļŠāļģāļŦāļĢāļąāļāļāļēāļĢāļŠāļĢāđāļēāļāđāļāļāļāļģāļĨāļāļ.
- āļāļģāļāļēāļĢ Explore Data āļāđāļ§āļĒ Data Visualization Tools.
- āļŦāļēāļ§āļīāļāļĩāļāļēāļĢāļāļĢāļąāļāļāļĢāļļāļāļāļļāļāļ āļēāļāļāļāļāļāđāļāļĄāļđāļĨ āđāļĨāļ°āļŠāļĢāđāļēāļāļāļ§āļēāļĄāļāđāļēāđāļāļ·āđāļāļāļ·āļāļāļāļāļāđāļāļĄāļđāļĨāļāļđāđāļāļ§āđāļāđāļĄāđāļĨāļ° Patterns.
- āđāļāđ AI/ML āļāļēāļĢāļāļģāļāļēāļĒ āļāļēāļāļāļēāļĢāļāđ (Predictive) āđāļĨāļ°āļĢāļēāļĒāļāļēāļāļāļĨ.
- āļāļĢāļīāļāļāļēāļāļĢāļĩ āļŠāļēāļāļē āļ§āļīāļāļĒāļēāļāļēāļĢāļāļāļĄāļāļīāļ§āđāļāļāļĢāđ āļ§āļīāļĻāļ§āļāļĢāļĢāļĄāļĻāļēāļŠāļāļĢāđ āļāļāļīāļāļĻāļēāļŠāļāļĢāđ āļŠāļāļīāļāļī āļŦāļĢāļ·āļāļŠāļēāļāļēāļāļ·āđāļāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļ.
- āļĄāļĩāļāļĢāļ°āļŠāļāļāļēāļĢāļāđāđāļāļāļēāļĢāļāļģ Data Visualization.
- āļĄāļĩāļāļĢāļ°āļŠāļāļāļēāļĢāļāđāļāļēāļĢāđāļāđ Cloud Platform.
- āļĄāļĩāļāļĢāļ°āļŠāļāļāļēāļĢāļāđāļāļēāļĢāđāļāđ Python āđāļāđāļ Pandas, Numpy, Scikit-learn, Matplotlib and PyTorch.
- āļĄāļĩāļāļĢāļ°āļŠāļāļāļēāļĢāļāđ āļāļēāļĢāđāļāđ Machine Learning āđāļāđāļ regression, classification, clustering and association.
- āļĄāļĩāļāļ§āļēāļĄāđāļāđāļēāđāļāđāļāļŠāļāļīāļāļīāļāđāļāļĄāļđāļĨ.
- āļĄāļĩāļāļąāļāļĐāļ°āļāļēāļĢāļāļģāđāļŠāļāļ āđāļāļĒāļŠāļēāļĄāļēāļĢāļāļāļģāļāļ§āļēāļĄāļāļīāļāļāļĩāđāļāļąāļāļāđāļāļāļĄāļēāļāļģāđāļŦāđāđāļāđāļāļĢāļđāļāđāļāļāļāļĩāđāđāļāđāļēāđāļāļāđāļēāļĒ.
- āļāļąāļāļŠāļ·āđāļāļŠāļēāļĢāļāļĩāđāļāļĩāļāļĢāđāļāļĄāļāļēāļĢāļāļąāļāļāļēāļĢāļāļđāđāļĄāļĩāļŠāđāļ§āļāđāļāđāļŠāđāļ§āļāđāļŠāļĩāļĒāđāļāđ.
- āļĄāļĩāļāļąāļāļĐāļ°āļāļēāļĢāđāļāđāļāļąāļāļŦāļē.
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