Data Scientist – Card Products & Loyalty

We are looking for a
Data Scientist
with a strong background in predictive modeling, customer segmentation, and loyalty analytics related to card products (credit/debit). You will work closely with cross- functional teams to develop data- driven solutions that enhance card usage, optimize reward programs, and support strategic initiatives such as cross- sell, retention, and churn prevention. You will be responsible for building models, validating hypotheses, and turning complex data into actionable insights that drive business impact.

Conduct customer segmentation using clustering, RFM, and other statistical methods.
Analyze card transactions, spending patterns, and loyalty behavior to detect trends and risks.
Collaborate with Product, Marketing, and CRM teams to design and evaluate A/B tests and targeting strategies.
Translate complex analytical results into business- friendly insights.
Contribute to model governance, data quality, and responsible AI practices.
Build data pipelines and monitor model performance post- deployment.
Develop and maintain machine learning models for use cases such as churn prediction, credit scoring, card usage forecasting, cross- sell propensity, and campaign personalization etc.

Required Qualifications:

Familiarity with lifecycle management of models in Amazon SageMaker.
Proficient in Python and SQL for data analysis and modeling.
Strong communication and storytelling skills, both written and verbal.
Good understanding of customer lifecycle, card usage, and financial products.
Hands- on experience with data warehouses (Snowflake, Redshift, S3) and cloud platforms (AWS preferred).
Strong knowledge of machine learning libraries (e.g., scikit- learn, XGBoost, LightGBM).
3+ years of experience in Data Science, preferably in Banking, Fintech, or Loyalty.

Nice to Have:

Experience integrating models into APIs or CEP platforms like MoEngage.
Experience in mentoring junior team members or working within data squads.
Familiarity with orchestration and automation tools (e.g., Airflow, MLflow).
Knowledge of attribution modeling, uplift modeling, or time- series forecasting.

BENEFITS:

Competitive salary package (Base salary and performance bonuses).
Provision of work equipment (Macbook/ Laptop, mouse, monitor, etc.).
Comprehensive health and accident insurance.
Probation period salary is 100% of the official salary.
A creative and modern working environment.
15 days of annual leave.

Laptop, Chế độ bảo hiểm, Phụ cấp, Đồng phục, Chế độ thưởng, Chăm sóc sức khỏe, Đào tạo, Tăng lương, Công tác phí, Nghỉ phép năm, CLB thể thao

Cập nhật gần nhất lúc: 2025-09-19 05:35:02