Job Purpose

The company is executing a multi-year Analytics & AI roadmap spanning 70+ enterprise projects across traditional analytics, machine learning, Generative AI / LLM use cases, and third-party data integration. This role will directly support the Chief Risk Officer in scaling execution of this roadmap by working alongside and assisting existing analytics team members & external vendors on model development, data preparation, and project delivery. The role requires someone who can operate independently on well-defined analytical tasks, support more complex modelling work led by senior team members, and help maintain delivery discipline across a large, concurrent project portfolio.

This role is expected to play a pivotal role in scaling the company's analytics capability from a small, high-caliber team into an enterprise-wide function.

Collaboration

The candidate will deal with various stakeholders like Finance, Operation (Underwriting, Claims, Persistency), Governance team, Various Distribution Channels & IRDAI.

Principal

Responsibilities

1. Support end-to-end execution of projects on the Analytics & AI roadmap from requirement scoping through model build, validation, and deployment support.

2. Build and maintain machine learning models for use cases such as lapse/persistency prediction, early-claim and fraud risk scoring, lead prioritization, and underwriting risk assessment etc

3. Assist in evaluating and integrating third-party data sources (e.g., CRIF, eKYC, PIVC, other unstructured datasets) into analytics pipelines and models.

4. Support testing of Generative AI / LLM use cases.

5. Perform data extraction, cleaning, and querying (SQL / Amazon Athena) and build automation scripts (Python)



to consolidate and process data from multiple sources.

6. Prepare and maintain project trackers, status dashboards, and MIS for review by the CRO and senior stakeholders

7. Support model documentation, explainability write-ups, model validation framworks and governance artefacts required for IRDAI compliance and internal audit.

8. Assist in translating business requirements from Sales, Underwriting, Claims, and Persistency teams into analytical/technical specifications.

Requirements

Qualification & Experience:

1. Bachelor's or Master's degree in Statistics, Mathematics, Data Science, Computer Science, Engineering, Economics, or a related quantitative discipline.

2. 47 years of relevant experience in analytics, data science, or MIS/reporting roles; prior BFSI or insurance industry experience is strongly preferred.

3. Demonstrated experience building and deploying statistical or machine learning models in a production or business-facing setting.

Technical Skills:

1. Positive Communication Skills

2. Proficiency in Python for data analysis and ML model development (pandas, scikit-learn or equivalent).

3. Advanced Excel skills for model building, automation, and business reporting.

4. Working knowledge of core ML techniques (classification, regression, propensity/risk scoring).

5. Familiarity with Generative AI / LLM concepts and tools (e.g., document summarization, chatbot frameworks) is a plus, though not mandatory at entry.

6. Exposure to visualization tools (e.g., Power BI, Tableau) is an advantage.

Desired Attributes:

1. Ability to work independently on assigned modules while supporting senior team members on larger, complex initiatives.

2. Strong Communication Skills

Job Location

Hyderabad – Full time

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