Filter Jobs

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.

Skills:

ETL, Python, TensorFlow

Job type:

Full-time

• Develop and deploy machine learning models for demand forecasting, customer segmentation, pricing optimization, and inventory management.
• Work with large-scale datasets and implement efficient feature engineering pipelines to enhance model performance.
• Use PySpark to process and analyze large datasets in a distributed computing environment.
• Collaborate with data engineers to build scalable data pipelines and ensure data quality.
• Implement MLOps best practices for model deployment, monitoring, and retraining in production.
• Design ETL workflows for preprocessing and transforming structured and unstructured data.
• Communicate findings and recommendations to business stakeholders in a clear and actionable manner.
• Stay up to date with the latest advancements in AI, machine learning, and data engineering.
• 5+ years of experience in data science, machine learning, or applied AI.
• Strong programming skills in Python (pandas, NumPy, scikit-learn, TensorFlow/PyTorch).
• Hands-on experience with PySpark for big data processing and analysis.
• Experience with SQL for querying large datasets efficiently.
• Familiarity with cloud platforms (AWS, GCP, Azure) and distributed computing frameworks.
• Knowledge of MLOps practices (model versioning, CI/CD for ML, monitoring, automation).
• Experience working with ETL workflows and data engineering pipelines.
• Strong understanding of statistical analysis, time-series forecasting, and clustering techniques.
• Excellent problem-solving and communication skills, with the ability to translate data insights into business value.
• Experience in the retail industry or working with e-commerce/consumer data.
• Familiarity with tools like Databricks, Airflow, MLflow, and Docker/Kubernetes.
• Experience with deep learning frameworks for NLP or computer vision.
• 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:

Data Analysis, Statistics, Python

Job type:

Full-time

• Data Analysis: Collect, preprocess, and analyze large datasets to identify trends and actionable insights for retail business challenges..
• Model Development: Design, train, and deploy machine learning models for tasks such as demand forecasting, customer behavior analysis, and inventory optimization..
• Collaboration: Partner with cross-functional teams, including data engineers and business stakeholders, to translate requirements into data-driven solutions..
• Visualization and Communication: Present insights and findings through visualizations and dashboards to inform decision-making..
• Innovation: Stay updated on the latest tools and techniques in data science and retail analytics..
• Engineer and optimize features to improve machine learning model performance.
• Automate feature extraction pipelines for scalable workflows.
• Contribute to the deployment, monitoring, and retraining of machine learning models in production environments.
• Assist in designing and maintaining data pipelines and ensuring data quality..
• Education: Bachelor s or Master s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field..
• Experience: At least 2 years of experience in data science or a related field..
• Proficiency in Python for data analysis and machine learning.
• Strong SQL skills for managing and querying large datasets.
• Experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
• Knowledge of data visualization tools (e.g., Tableau, Power BI, matplotlib).
• Soft Skills: Strong problem-solving, communication, and teamwork abilities..
• Exposure to MLOps tools (e.g., MLflow, Kubeflow, AWS SageMaker).
• Familiarity with data engineering tools (e.g., Apache Spark, Kafka, Airflow).
• Experience in building real-time analytics or personalization systems.

Job type:

Full-time

• ออกแบบและดำเนินการวิเคราะห์ข้อมูลเชิงลึก เพื่อสนับสนุนกลยุทธ์องค์กร และเพิ่มประสิทธิภาพการดำเนินงาน.
• สร้าง Dashboard และรายงานแบบ Interactive โดยใช้ Power BI หรืออื่นๆ.
• สร้าง Framework สำหรับการวิเคราะห์ข้อมูลแบบ End-to-End ตั้งแต่การเก็บข้อมูล ไปจนถึงการนำเสนอผลลัพธ์.
• สร้างแบบจำลองทางสถิติ (Predictive Model) เช่น Sales Demand Forecasting, Fuel Consumption Trends, Customer Lifetime Value.
• ทำงานร่วมกับธุรกิจ ในการแปลปัญหาทางธุรกิจให้เป็นโจทย์การวิเคราะห์ข้อมูล พร้อมนำเสนอ Insight ที่มี Impact.
• ร่วมกำหนด KPI และ Data Strategy กับหน่วยงานธุรกิจ.
• สื่อสารผลการวิเคราะห์ให้เข้าใจง่าย พร้อมข้อเสนอแนะเชิงกลยุทธ์ที่นำไปปฏิบัติได้.
• ปริญญาตรีขึ้นไปในสาขา Data Science, Statistics, Computer Science, Business Analytics หรือสาขาอื่นที่เกี่ยวข้อง.
• มีประสบการณ์อย่างน้อย 2-5 ปีในด้าน Data Analytics หรือ Data Science.
• มีประสบการณ์ด้าน Data Visualization และสามารถนำเสนอข้อมูลได้อย่างมีประสิทธิภาพ.
• มีทักษะการเขียนโปรแกรม เช่น Python, R, SQL และเครื่องมือ BI เช่น Power BI, Tableau หรือใกล้เคียง.
• มีทักษะการสื่อสารและการคิดเชิงวิเคราะห์ (Analytical Thinking) ที่ยอดเยี่ยม.
• เข้าใจแนวคิด Machine Learning และสามารถใช้ Libraries เช่น scikit-learn, XGBoost, TensorFlow, PyTorch ได้.
• มีความรู้ความเข้าใจเกี่ยวกับการทำ Forecasting, Clustering และ Predictive Analytics.
• หากมีประสบการณ์กับ Cloud Platform (เช่น AWS, GCP, Azure) จะพิจารณาเป็นพิเศษ.

Skills:

Python, SQL

Job type:

Full-time

• ปฏิบัติงานยัง บริษัท Infinitas by Krungthai
• We are seeking a Data Scientist specializing in credit decision engine development to drive data-driven lending decisions and risk assessment. The ideal candidate will combine strong analytical skills with deep understanding of credit process.
• Model Development & Deployment
• Develop and maintain credit risk assessment and lending decisions modules
• Expertise for handling large financial databases and credit data manipulation
• Design and implement credit-risk decisioning model solutions using API-based frameworks (e.g., Flask,
• Fast API) or event-driven architecture (e.g., Kafka, Pub/Sub), along with other suitable technologies
• Monitor model performance to ensure high accuracy and reliability in credit decisions Data Analysis & Risk Assessment
• Clean and preprocess financial datasets, particularly credit lending and risk data
• Conduct advanced statistical analyses to support risk assessment and lending decisions.
• Technical Skills
• Proficiency in Python, SQL, and machine learning libraries (TensorFlow, PyTorch, Scikit-Learn)
• Experience with cloud platforms (AWS,GCP) for model deployment
• Knowledge of statistical and machine learning techniques for risk modeling Domain Expertise
• Understanding of credit lending and risk assessment principles
• Experience in financial data analysis within regulatory constraints
• Proven track record in developing credit decision engines (optional)Education & Experience
• Bachelor s degree or higher in Statistics, Computer Science, Mathematics, or related field
• Minimum 3 years experience in retail lending or similar role Additional Requirements
• Strong communication skills for presenting complex findings and process flow to management
• Experience with data visualization tools (Tableau, Power BI)
• Ability to work collaboratively with cross-functional teams.
• You have read and reviewed Infinitas By Krungthai Company Limited's Privacy Policy at https://krungthai.com/Download/download/DownloadDownload_73Privacy_Policy_Infinitas.pdf. 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.".