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.
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. Good 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