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Salary
≈ $22k – $47k per year (Estimated)
Location
In office (Bengaluru)
Experience
6+ years exp
Employment
Full-Time

First seen by Alion on Oct 24, 2026.

Overview
Company
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Aon

Aon is a global professional services firm that helps clients make better decisions on risk, insurance and related services. It recruits insurance study and tender project managers in France as well as software engineers, solution architects and DevOps staff in Bengaluru. The company is headquartered in Dublin, Ireland.
Backed by ROPEA
Job Title- Senior Actuarial Data Scientist

Position type- Full Time

Work Location- Bengaluru

Working style- Hybrid

Shift Time- 12PM to 9PM

People Manager role: No

Required education and certifications critical for the role- Bachelor's/Master's degree in Computer Science, Data Science, Statistics, Mathematics, Software Engineering, or related quantitative field.

Required Years Of Experience –

6-10 years of work experience in relevant field

AON IS IN THE BUSINESS OF BETTER DECISIONS

At Aon, we shape decisions for the better to protect and enrich the lives of people around the world.

As an organization, we are committed to our purpose as one firm, united through trust as one inclusive, diverse team and we are passionate about helping our colleagues and clients succeed.

Information About The Business

Aon Data & Analytics team is hiring a Senior AI/Data Scientist, based in Bangalore. You will work with global, cross-functional teams to design, build, and scale data products and generative AI solutions that power better decisions for Aon and our clients across the insurance and Insurtech landscape.

Key Tasks & Responsibilities

  • 5+ years of experience as an AI/Data Scientist delivering end-to-end data science and machine learning solutions, with hands-on development in Python.
  • Must have: Databricks experience (Delta Lake, Spark, notebooks/jobs, MLflow, Unity Catalog), including building production-grade pipelines and ML workflows.
  • Must have: Insurance/Insurtech industry experience — practical exposure to insurance data, workflows, and business problems. Familiarity with frequency/severity modelling concepts and actuarial analytics is highly valued (formal actuarial qualifications are not required).
  • Design, build, and maintain ETL/ELT pipelines and curated datasets; ensure data quality, lineage, and observability across batch/streaming workloads.
  • Fine-tune and optimize LLMs (parameter-efficient fine-tuning, prompt tuning) and implement Retrieval-Augmented Generation (RAG) with robust evaluation (quality, safety, latency, cost).
  • Collaborate with internal teams to design and implement robust, scalable data and GenAI solutions.
  • Ability to build and scale products from scratch.

Good-to-Have Skills

  • Experience building and deploying agentic workflows including tool/function calling and guardrails.
  • Experience orchestrating data/ML workflows (Databricks Workflows, ADF) and implementing CI/CD for notebooks, jobs, and pipelines.
  • Strong understanding of analytics engineering/BI concepts (dimensional modeling, semantic layers, dashboarding) and partnering with stakeholders to define metrics.
  • Hands-on with vector databases and search and building document ingestion/indexing pipelines for RAG.
  • Experience with LLM evaluation/experimentation (A/B tests, offline eval sets, hallucination checks), prompt/RAG testing, and responsible AI practices.
  • Experience with GenAI platforms such as Databricks Genie Spaces, Azure AI Foundry, Microsoft Copilot Studio, and/or Gemini for Google Workspace (designing assistants, grounding, integrations, and governance).
  • Experience applying data science and ML to insurance use cases such as claims analytics, risk scoring, pricing models, or loss reserving is a strong differentiator.

Personal Attributes

  • A team player with good interpersonal skills.
  • Strong problem-solving and communication skills.
  • A self-motivator and a collaborative team player.
  • Excellent time management skills and the ability to assume leadership roles when necessary.
  • Agile, action oriented and a quick learner.
  • Out of box thinker.

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