StashFin - Manager - Data Science & Analytics (4-7 yrs)

Location : Gurugram

Department : Data Science & Analytics

Reports to : Senior Manager - Data Science

Experience Required : 4-7 years in applied data science, machine learning, or statistical modeling roles, preferably in fintech, consumer tech, or financial services.

Role Overview :

We are looking for a Manager - Data Science to build scalable models and frameworks that power growth, engagement, and decision-making across the Stashfin ecosystem. You'll work closely with the Senior Manager - Data Science and collaborate with product, marketing, credit, and engineering teams to design experiments, predictive models, and data solutions that directly impact business outcomes.

Key Responsibilities:

Model Development & Deployment:

- Design, build, and deploy machine learning models for churn prediction, credit usage, user segmentation, and lifetime value estimation.

- Own end-to-end lifecycle of data science projects - from problem definition and data exploration to modeling, validation, and production deployment.

- Work on real-time scoring models, recommendation engines, and personalization algorithms to enhance app experience and business efficiency.

Experimentation & Uplift Measurement:

- Partner with growth, CRM, and product teams to define and run A/B/n tests and experiments.

- Measure uplift and incremental value of marketing and product interventions using robust causal inference techniques.

Advanced Analytics & Insights:

- Analyze structured and unstructured data to extract patterns and behaviors.

- Build actionable dashboards and model outputs that support marketing, risk, and product decisions.

- Translate business problems into statistical frameworks and deliver decision-ready insights.

Tools, Frameworks & Pipelines:

- Write clean, production-ready code in Python or R, using libraries like scikit-learn, XGBoost, or TensorFlow.

- Collaborate with data engineering teams to create ETL pipelines, model APIs, and real-time data streams.

- Use platforms like BigQuery, Airflow, Databricks, and model versioning tools for seamless deployment.

Cross-Functional Collaboration:

- Work closely with business teams to scope problems, define KPIs, and translate models into action.

- Collaborate with BI teams to bring model outcomes into dashboards and business monitoring tools.

Qualifications & Skills:

- 4-7 years of experience in data science, ML engineering, or applied statistical modeling.

- Strong command over Python, SQL, and common ML libraries (e.g., pandas, scikit-learn, XGBoost, LightGBM).

- Experience with model evaluation, hyperparameter tuning, and performance optimization.

- Good understanding of probability, statistics, and experimental design.

- Familiarity with cloud environments like GCP, AWS, or Azure is a plus.

- Experience in fintech, lending, credit scoring, or user behavior modeling is highly desirable.

What You'll Get:

- Opportunity to solve real-world problems at scale in India's leading credit fintech platform.

- A collaborative team culture with cutting-edge tools and high business impact.

- Exposure to both marketing and product modeling use cases.