Data Science Specialist

We are looking for a Data Science Specialist 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.
Key Responsibilities

Analyze card transactions, spending patterns, and loyalty behavior to detect trends and risks.
Conduct customer segmentation using clustering, RFM, and other statistical methods.
Collaborate with Product, Marketing, and CRM teams to design and evaluate A/B tests and targeting strategies.
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.
Translate complex analytical results into business- friendly insights.
Contribute to model governance, data quality, and responsible AI practices.

Required Qualifications

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

Nice to Have

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

What We Offer

Flexible working environment and continuous learning opportunities.
Access to rich datasets across banking and loyalty systems.
Opportunities to work on impactful, large- scale data initiatives.
A data- driven culture supported by Product and Engineering teams.

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

Cập nhật gần nhất lúc: 2025-10-28 06:00:06