Senior Data Scientist (Machine Learning Engineer) True Money

Ascend Group Co., Ltd. (Bangkok)

Bangkok

Bangkok, Thailand

Ascend Group is a privately owned e-commerce company headquartered in Bangkok, Thailand as a spin-off of True Corporation. It marked its $150-million expansion by launching their affiliates in the Philippines and Indonesia, Vietnam, and also hard to reach economies like Myanmar and Cambodia.

About this position

We are seeking a highly motivated and curious individual who is passionate about solving complex lending challenges through innovative solutions. The ideal candidate will leverage their expertise in data querying, design, and analysis to transform complex data into user-friendly insights that are easily understood by business units and stakeholders. Strong teamwork, communication, and presentation skills are essential for this role. Successful candidates will report directly to the Machine Learning Team Lead.

Responsibilities

• Develop machine learning models, including credit, income estimation, and fraud detection models.
• Conduct research on cutting-edge technologies to improve existing model performance.
• Perform feature engineering on existing datasets, such as telecom data, retail data, and loan approval data.
• Create sentiment analysis models to support collection strategies.

Requirements

• Bachelor’s degree in Computer Science, Operations Research, Engineering, or a related quantitative field.
• 2-5 years of experience with programming languages such as Python, PySpark, SQL, or Scala.
• 5+ years of hands-on experience in developing and implementing AI/ML solutions (for senior roles).
• Proficiency with Python libraries, including Numpy, scikit-learn, OpenCV, TensorFlow, PyTorch, Flask, and Django.
• Experience with version control systems like Git or Bitbucket.
• Strong knowledge of REST APIs, Docker, Google BigQuery, VS Code, and Databricks.
• Strong analytical and data-driven mindset.
• Solid understanding of quantitative analysis methods in the context of financial institutions.
• Ability to effectively communicate modeling results to diverse audiences.
• Familiarity with MLOps concepts.
• Experience with projects involving telecommunication data will be greatly advantageous.