Job Summary

We are seeking a detail oriented and analytical qualified with atleast 2-3 years of experience in Data analytics ML modeling.

Responsibilities

- Build and monitor ML-based propensity models for Home Loan acquisition and cross-sell, and define bureau and non-bureau risk interventions within the offer construct - enabling risk-calibrated, analytics-led targeting across a large customer franchise.
- Develop, validate and refresh ML propensity models for HL fresh acquisition, balance transfer and cross-sell using bureau, demographic, behavioral and interaction data.
- Create derived and bucketed variables; run IV/WOE, correlation and stability checks to select robust, business-interpretable features.
- Track lift, rank-ordering, PSI/drift and out-of-sample performance; recalibrate models on defined cycles.
- Define offer-level risk rules using bureau signals (score, DPD, enquiries, utilization, vintage) and non-bureau signals (engagement, digital behavior, lead source, CRM activity).
- Recommend offer amount sharpening, eligibility overlays, verification triggers and suppression logic to balance penetration with portfolio quality.
- Build simple, non-overlapping, business-readable decision rules and segments that can be directly operationalized by business teams.
- Write production-grade SQL and Python pipelines for data extraction,



scoring and refresh; ensure data accuracy and governance.
- Build monitoring dashboards and MIS on offer penetration, conversion, model performance and risk outcomes.
- Partner with Business, Risk, Product, Campaigns, IT and bureau partners; present findings and recommendations clearly.

Major Challenges

Technology changes

Key Decisions / Dimensions

Decisions: Mention the key decisions taken by the job holder at his end and the decisions for which the job holder goes to superior with options and recommendations or seek approval. Dimensions: List the significant numerical data which will reflect the scope and scale of activities concerning this job. Financial Dimensions: These should be quantifiable numerical amounts like annual budgets, project costs, annual revenue, purchase value, number of transactions, etc.

Qualifications

- Educational Qualifications: Graduate or Post-Graduate, Graduate with 2-3 years of experience, post graduate with atleast 2-3 years of experience
- Experience either in financial sector or in a different sector with similar job role
- Must have prior experience of business development or handling business stakeholders and partners
- Must be proficient in Machine Learning, Python, SQL

Skills

- Entrepreneurship skills
- Stakeholder management
- Agile
- Persistence
- Business development

📌 Unit Manager - IT (Pune)
🏢 Bajaj Finance
📍 Pune