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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. .