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Skills:

Statistics, Big Data, SQL

Job type:

Full-time

• 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.

Skills:

Data Analysis, Big Data, Statistics, English

Job type:

Full-time

• Work collaboratively with data engineers and data architects to acquire new data from internal and external source systems.
• Support business initiatives and projects by performing data wrangling and exploratory data analysis, discovering trends and patterns, building predictive models and machine learning algorithms, etc., based on the CRISP-DM methodology and agile approach.
• Stay up to date with big data and analytical techniques, such as machine learning, d ...
• Provide analytics expertise, directions and guidance to business leads through turning insights into business action so as to improve sales and customer profitability.
• Present summary of analyses including data monetization on large datasets using advanced analytics tools and data visualization techniques.
• Lead implementation of AI models and business rules incorporated in automated business processes.
• Bachelor's degree or higher in Data Science, Statistics or related fields.
• AI and machine learning professional certification.
• More than 3-5 years of experience in data science and big data using tools, e.g., SPSS, SAS, Alteryx, Spark, Jupyter Notebook and Databricks.
• Excellence communication in Thai and English.

Skills:

Sales, Finance, Statistics

Job type:

Full-time

• Drive the end-to-end AI and Advanced Analytics initiatives to support CP Axtra s Retail & Wholesale businesses.
• Develop and execute a forward-looking AI strategy that delivers measurable impact on revenue growth, cost efficiency, and customer engagement.
• Serve as a bridge between business and technology, ensuring AI adoption and scaling across multiple business units.
• Stay updated on global and local AI trends, including Generative AI, personalization, forecasting, and optimization, to strengthen CP Axtra s competitive edge.
• Analytics and AI Execution.
• Lead the design, development, and deployment of machine learning and AI models, including personalization engines, pricing optimization, demand forecasting, inventory management, and GenAI/NLP applications.
• Oversee experimentation, validation, and monitoring of AI/ML models to ensure scalability, reliability, and business integration.
• Ensure close collaboration with data engineering teams to enable robust pipelines and MLOps for production-grade solutions.
• Business Partnership.
• Partner with Retail Operations, Marketing, Sales, Supply Chain, Finance, and IT to co-create AI use cases and drive adoption.
• Build strong relationships with stakeholders to align priorities, communicate trade-offs, and manage expectations effectively.
• Act as a trusted advisor to senior executives, translating complex AI insights into actionable recommendations.
• Evangelize the value of AI and data-driven decision-making across the organization.
• People Leadership and Collaboration.
• Mentor and coach a team of data scientists and analysts, fostering a culture of innovation, experimentation, and continuous learning.
• Promote cross-functional collaboration with Business Intelligence and Data Engineering teams to deliver integrated solutions.
• Encourage knowledge sharing and build internal AI/ML capability to strengthen organizational maturity.
• Performance Monitoring and Optimization.
• Define and monitor success metrics for AI initiatives, such as sales uplift, campaign ROI, operational cost reduction, and customer lifetime value.
• Continuously assess and optimize AI-driven processes to maximize business impact.
• Share learnings, case studies, and success stories to build trust and ensure alignment with business leaders.
• Bachelor s degree in Statistics, Mathematics, Computer Science, Data Science, Economics, or a related field (Master s or PhD strongly preferred).
• 5+ years of experience in data science, advanced analytics, or AI applications (experienced in Retail or Wholesale domain preferred).
• Proven experience delivering AI/ML solutions from ideation to production with measurable business outcomes.
• Proficiency in Python, R, SQL, and machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
• Familiarity with GenAI and NLP frameworks (e.g., LLMs, LangChain, RAG pipelines).
• Familiarity with cloud-based data platforms (e.g., AWS, GCP, Azure) and big data technologies (e.g., Spark, Hadoop, Databricks).
• Experience with data visualization tools (e.g., Power BI, Tableau) and modern MLOps practices.
• Strong stakeholder management and communication skills across technical and business functions.
• Proven ability to prioritize and deliver projects with business impact.
• Understanding of retail and wholesale operations, including customer journey, pricing, promotion, assortment, and supply chain optimization.
• Demonstrated success in driving AI adoption, gaining executive buy-in, and scaling solutions across organizations.
• 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. .

Skills:

Power BI, Tableau, Statistics

Job type:

Full-time

• Identify valuable data sources and automate data collection processes.
• Undertake preprocessing and transformation of structured and unstructured data.
• Analyze large datasets to discover meaningful trends, patterns, and business insights.
• Build and deploy predictive models, machine learning algorithms, and NLP models (classification, clustering, topic modeling, sentiment analysis).
• Combine models through ensemble techniques to improve accuracy.
• Design and maintain end-to-end data pipelines and migrate workflows to cloud platforms (e.g., Databricks, BigQuery, PySpark).
• Develop and maintain dashboards (Power BI, Looker, Tableau) to communicate insights effectively.
• Collaborate with cross-functional teams including product, engineering, and business stakeholders to align data solutions with business needs.
• Propose solutions and strategies to address complex business challenges.
• QualificationsBachelor s or Master's degree in Data Science, Statistics, or related field.
• Proven experience as a Data Scientist or Data Analyst, with demonstrated success in building and deploying data-driven solutions.
• Strong proficiency in Python, SQL, PySpark; experience with big data platforms (Databricks, BigQuery, Redshift, Hadoop).
• Solid understanding of machine learning and deep learning frameworks.
• Experience in data mining, feature engineering, and statistical modeling.
• Strong math and statistical skills; analytical mindset with problem-solving aptitude.
• Excellent communication and presentation skills to engage with both technical and non-technical stakeholders.
• (Preferred) Experience with stream processing, NLP, and scalable big data stores.
• Applicants can read the Personal Data Protection Announcement of the Bank's Human Resources Function by typing the link from the image that stated below.
• EN: (https://krungsri.com/b/privacynoticeen).
• ผู้สมัครสามารถอ่านประกาศการคุ้มครองข้อมูลส่วนบุคคลส่วนงานทรัพยากรบุคคลของธนาคารได้โดยการพิมพ์ลิงค์จากรูปภาพที่ปรากฎด้านล่าง.
• ภาษาไทย: (https://krungsri.com/b/privacynoticeth).
• หมายเหตุ ธนาคารมีความจำเป็นและจะมีขั้นตอนการตรวจสอบข้อมูลส่วนบุคคลเกี่ยวกับประวัติอาชญากรรมของผู้สมัคร ก่อนที่ผู้สมัครจะได้รับการพิจารณาเข้าร่วมงานกับธนาคารกรุงศรีฯ.
• Remark: The bank needs to and will have a process for verifying personal information related to the criminal history of applicants before they are considered for employment with the bank..

Skills:

Research, Python, SQL, English

Job type:

Full-time

• Generate insights and provide actionable recommendations by applying statistical and machine learning methods to large and complex datasets.
• Solve complex technical and business problems using advanced analytical methods.
• Work with engineering teams to implement end-to-end processes, from model development to testing, validation, and deployment.
• Research and develop new quantitative models and frameworks to enhance the company s data science capabilities.
• Basic Qualifications Bachelor s degree in Engineering, Computer Science, Mathematics, Physics, Statistics, or another highly quantitative field.
• Experience with statistical programming languages (e.g., Python, R, Pandas) and database software (e.g., SQL, PySpark).
• Knowledge of statistics (e.g., hypothesis testing, regression) and machine learning.
• Strong analytical and problem-solving skills.
• Preferred Qualifications Master s or Ph.D. 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).
• Strong coding skills or a software development background.
• Ability to think independently and communicate complex ideas to non-technical stakeholders.
• Excellent command of English, both verbal and written.
• 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.

Experience:

2 years required

Skills:

Research, Python, SQL

Job type:

Full-time

• 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.

Experience:

4 years required

Skills:

Statistics, Python, SQL

Job type:

Full-time

• 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.