เงื่อนไขการค้นหา

ทักษะ:

Statistics, Python, SQL

ประเภทงาน:

งานประจำ

• Bachelor s or Master s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
• 7+ years of experience in data science, machine learning, and predictive analytics, preferably in the banking or financial services industry.
• Strong expertise in Python, R, SQL, and big data frameworks (Spark, Hadoop).
• Hands-on experience with ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn).
• Proven track record of developing and deploying ML models in production environments.
• Experience working with cloud platforms (AWS, Azure, GCP) and MLOps tools.
• Strong knowledge of statistical modeling, time-series forecasting, NLP, and deep learning techniques.
• Excellent problem-solving skills and ability to communicate complex data insights to non-technical stakeholders.
• Experience in credit risk modeling, fraud detection, or financial forecasting.
• Knowledge of graph analytics, reinforcement learning, or advanced optimization techniques.
• You have read and reviewed Krung Thai Bank Public Company Limited's Privacy Policy at https://krungthai.com/th/content/privacy-policy. The Bank does not intend or require the processing of any sensitive personal data, including information related to religion and/or blood type, which may appear on copy of your identification card. Therefore, please refrain from uploading any documents, including copy(ies) of your identification card, or providing sensitive personal data or any other information that is unrelated or unnecessary for the purpose of applying for a position on the website. Additionally, please ensure that you have removed any sensitive personal data (if any) from your resume and other documents before uploading them to the website. The Bank is required to collect your criminal record information to assess employment eligibility, verify qualifications, or evaluate suitability for certain positions. Your consent to the collection, use, or disclosure of your criminal record information is necessary for entering into an agreement and being considered for the aforementioned purposes. If you do not consent to the collection, use, or disclosure of your criminal record information, or if you later withdraw such consent, the Bank may be unable to proceed with the stated purposes, potentially resulting in the loss of your employment opportunity with the Bank. .

ทักษะ:

Research, Statistics, Python, English

ประเภทงาน:

งานประจำ

• 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.

ประสบการณ์:

1 ปีขึ้นไป

ทักษะ:

Data Analysis, Digital Marketing, Industry trends

ประเภทงาน:

งานประจำ

• Department: Information Technology.
• Company: บริษัท จีเอ็มเอ็ม มิวสิค จำกัด (มหาชน).
• Perform large-scale data analysis and develop effective statistical model for time series, segmentation, classification, pattern recognition, optimization, etc. on digital data (e.g., Web, App, Line, other media platform etc.).
• Develop, build and test statistical and computational models that serve as a key input for digital marketing tools.
• Identify actionable insights and suggest recommendation for data-driven marketing campaigns.
• Communicate findings and build buy-in with key stakeholders through data visualizations.
• Interact and collaborate with product and marketing managers to provide impactful analysis and insights that align with business objectives.
• Work closely with other BI functions, data analyst and campaign operations to provide end-to-end analytical solutions and proactively create and test decision rules for digital marketing campaigns.
• Collaborate with internal teams on defining population segments to support personalized consumer experiences.
• Provide business requirements and collaborate with internal teams on data capture strategy that will support advanced analysis and insights on consumer behavior.
• Provide ongoing insight into industry trends in web & app analytics, site optimization, and customer segmentation.
• 1-3 years of experience in Data Scientist for solving analytical problems using quantitative approaches.
• Excellent understanding of fundamentals of statistics.
• Advanced in Python.
• Strong experimental design and analysis skills.
• Familiar with time series analysis, forecasting, and machine learning techniques, previous hands-on experience is a plus.
• Ability to manipulate and analyzing complex, high-volume, high-dimensionality data from varying sources.
• Ability to communicate complex analysis in a clear, simple, and actionable manner.
• Working knowledge of SQL and relational databases and analysis tool.
• ประสบการณ์ 2 ปีขึ้นไป.
• จำนวน 1 อัตรา.

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

SQL, Python, English

ประเภทงาน:

งานประจำ

• 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.
• ท่านสามารถอ่านและศึกษานโยบายความเป็นส่วนตัวของธนาคารกรุงไทย จำกัด (มหาชน) ที่ https://krungthai.com/th/content/privacy-policy ทั้งนี้ ธนาคารไม่มีเจตนาหรือความจำเป็นใดๆ ที่จะประมวลผลข้อมูลส่วนบุคคลที่มีความอ่อนไหว รวมถึงข้อมูลที่เกี่ยวข้องศาสนาและ/หรือหมู่โลหิต ซึ่งอาจปรากฏอยู่ในสำเนาบัตรประจำตัวประชาชนของท่านแต่อย่างใด ดังนั้น กรุณาอย่าอัปโหลดเอกสารใดๆ รวมถึงสำเนาบัตรประจำตัวประชาชน หรือกรอกข้อมูลส่วนบุคคลที่มีความอ่อนไหวหรือข้อมูลอื่นใด ซึ่งไม่เกี่ยวข้องหรือไม่จำเป็นสำหรับวัตถุประสงค์ในการสมัครงานไว้บนเว็บไซต์ นอกจากนี้ กรุณาดำเนินการให้แน่ใจว่าได้ดำเนินการลบข้อมูลส่วนบุคคลที่มีความอ่อนไหว (ถ้ามี) ออกจากเรซูเม่และเอกสารอื่นใดก่อนที่จะอัปโหลดเอกสารดังกล่าวไว้บนเว็บไซต์แล้วด้วย ทั้งนี้ ธนาคารมีความจำเป็นต้องเก็บรวบรวมข้อมูลส่วนบุคคลเกี่ยวกับประวัติอาชญากรรมของท่านเพื่อบรรลุวัตถุประสงค์ในการพิจารณารับบุคคลเข้าทำงาน หรือการตรวจสอบคุณสมบัติ ลักษณะต้องห้าม หรือพิจารณาความเหมาะสมของบุคคลที่จะให้ดำรงตำแหน่ง ซึ่งการให้ความยินยอมเพื่อเก็บรวบรวม ใช้ หรือเปิดเผยข้อมูลส่วนบุคคลเกี่ยวกับประวัติอาชญากรรมของท่านมีความจำเป็นสำหรับการเข้าทำสัญญาและการได้รับการพิจารณาตามวัตถุประสงค์ดังกล่าวข้างต้น ในกรณีที่ท่านไม่ให้ความยินยอมในการเก็บรวบรวม ใช้ หรือเปิดเผยข้อมูลส่วนบุคคลเกี่ยวกับประวัติอาชญากรรม หรือมีการถอนความยินยอมในภายหลัง ธนาคารอาจไม่สามารถดำเนินการเพื่อบรรลุวัตถุประสงค์ดังกล่าวข้างต้นได้ และอาจ ทำให้ท่านสูญเสียโอกาสในการได้รับการพิจารณารับเข้าทำงานกับธนาคาร .

ทักษะ:

Statistics, Data Analysis, SQL

ประเภทงาน:

งานประจำ

• Data Science Foundations: Strong foundation in data science, statistics, and advanced data analytics, including data visualization to communicate insights effectively.
• Exploratory Data Analysis (EDA): Skilled in performing EDA to uncover patterns, detect anomalies, and generate meaningful insights from data.
• Experimentation & Testing: Skilled in designing A/B tests or other experimental designs to measure business impact, analyze results, and communicate findings clearly to stakeholders.
• Machine Learning & AI.
• Model Development & Deployment: Experience in building, deploying, and optimizing machine learning models on large datasets.
• Generative AI (GenAI): Opportunity to work on GenAI projects that drive innovation and impactful business solutions.
• Problem-Solving & Collaboration.
• Analytical & Problem-Solving Skills: Strong analytical and problem-solving abilities focused on deriving actionable insights from data.
• Team Collaboration: Ability to work effectively both independently and as part of a collaborative team, contributing to shared project goals.
• Technical Expertise.
• Proficiency in Big Data Technologies: Expertise in Spark, PySpark, and SQL for large-scale data processing focused on feature creation for machine learning models and data analysis tasks.
• Programming Skills: Strong proficiency in Python for data analysis and machine learning (including libraries like Pandas, PySpark, Scikit-learn, XGBoost, LightGBM, Matplotlib, Plotly, Seaborn, etc.).
• Python Notebooks: Familiarity with Jupyter, Google Colab, or Apache Zeppelin for interactive data analysis and model development.
• Platform Experience: Experience in using PySpark on cloud platforms such as Azure Databricks or other platforms (including on-premise) is a plus.
• Education & Experience.
• Educational Background: Bachelor s or advanced degree in Data Science, Statistics, Computer Science, Computer Engineering, Mathematics, Information Technology, Engineering, or related fields.
• Work Experience: At least 2-3 years of relevant experience in Data Science, Analytics, or Machine Learning, with demonstrated technical expertise and a proven track record of driving data-driven business solutions.

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

Statistics, Finance, Risk Management

ประเภทงาน:

งานประจำ

• 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.

ทักษะ:

Data Analysis, Finance, SQL, English

ประเภทงาน:

งานประจำ

• 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 creation: Create data analytic model including both deterministic and machine learning model.
• AI vendors coordination: 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 and 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.
• Master's degree in Finance, Business, Engineering, or a related field.
• Strong business acumen, with a deep understanding of retail and wholesale business.
• 3+ 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 Visualisation (Tableau, PowerBI) is a plus.
• Excellent communication skills with the ability to convey complex findings to non-technical stakeholders.
• Fluent in Thai and English.
• Having a good attitude toward teamwork 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. .

ประสบการณ์:

2 ปีขึ้นไป

ทักษะ:

Research, Python, SQL

ประเภทงาน:

งานประจำ

• 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.

ประสบการณ์:

4 ปีขึ้นไป

ทักษะ:

Statistics, Python, SQL

ประเภทงาน:

งานประจำ

• Collaborate with cross-functional teams to identify and prioritize business opportunities that can be addressed through data-driven solutions.
• Extract insights from large and complex datasets using a variety of tools and techniques.
• Develop and deploy predictive models and algorithms using statistical AI/machine learning, deep learning and generative AI modeling.
• Present findings and recommendations to stakeholders in a clear and compelling manner.
• Implement data-driven solutions in various environments, including integration with existing systems and processes.
• Stay up to date on the latest development in data science and bring new idea and technology to the team.
• Monitor the performance of deployed models together with algorithms and continuously improve model accuracy over time.
• Bachelor s or Master s degree in data science, Computer Science, Statistics, or related field.
• 4+ years of experience as a Data Scientist, with a focus on industries.
• Descriptive Analytics.
• Predictive & Prescriptive Analytics (Machine learning, Forecasting, Optimization, choosing the best path).
• Strong programming skills in Python and SQL along with libraries and frameworks for machine learning and statistical test, and their variation among databases.
• Experience with statistical and machine learning techniques.
• Proficiency in optimizing large, complicated SQL statements and code versioning tools such as Git, Mercurial, SVN or others.
• Experience with data visualization tools such as Looker Studio, Tableau, and Power BI.
• Strong problem-solving and communication skills.
• Experience with Cloud technology and databases (Cloud AWS, Azure, GCP).
• Extensive knowledge of Customer relationship management, Customer experience, Next best action, Credit scoring, and Insight & pattern discovery.
• Location: True Digital Park, Bangkok.

ทักษะ:

Big Data, Research, Statistics

ประเภทงาน:

งานประจำ

• 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.