Sr Applied AI Data Scientist

Job Summary

Sr Data Scientist - GD07AE

We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future. The Small Business Applied AI team sits at the intersection of advanced analytics, AI innovation, and business strategy – delivering scalable, high impact solutions that enhance underwriting, product, and distribution in a dynamic competitive environment.

We design and deploy cutting‑edge AI and ML solutions that drive smarter decisions, operational efficiency, and competitive advantage at scale.

• Develop AI solutions:
  Create ML and generative AI systems for RAG pipelines, chatbots, classification, forecasting, and recommendation.
• Ensure alignment with enterprise standards, seamless integration, and secure scalability.
• Own the AI lifecycle from problem framing through deployment: data prep, modeling, evaluation, model change management, orchestration, observability, drift detection, and synthetic data generation.

• Drive execution from discovery to rollout by defining scope, milestones, and acceptance criteria; managing dependencies/risks; coordinating cross‑functional work streams; and maintaining clear status reporting, issue escalation, and delivery timelines.

• Partner closely with Product, Underwriting, Distribution, Risk, Legal, and Compliance to align AI initiatives with enterprise objectives and governance expectations.
• Translate complex model behavior and evaluation outcomes into clear, actionable business insights with defined success criteria (accuracy, cost, performance, reuse, ROI).
• Develop deep understanding of insurance business processes, data, and regulatory constraints, embedding domain taxonomies, access controls, and security into solution design.

• Proficiency in Python and SQL (ideally Snowflake); experience with pandas, numpy, scikit‑learn.
• Strong foundation in ML, deep learning, NLP; familiarity with PyTorch/Tensor Flow and generative AI.
• Experience with cloud tools (Google Vertex AI, AWS Sage Maker/Bedrock).
• Ability to build reproducible workflows using Jupyter and GIT.
• Competence in end‑to‑end modeling: requirements, experiment design, evaluation, production monitoring.
• Experience tracking forecasting metrics (MAPE/WAPE) and LLM evaluation.
• Understanding agentic AI pipelines and prompt engineering for language models.
• Ability to frame business problems with hypothesis‑driven approaches and experimentation.
• Excellent communicator—able to translate analytics into clear business narratives for stakeholders.

• Object‑oriented programming and Google ADK.
• Knowledge of embeddings and similarity (e.g., cosine‑similarity).
• Google Cloud Platform literacy.
• Advanced PyTorch/Tensor Flow skills.
• NLP & Generative AI: hybrid‑dense retrieval, chunking, structured outputs.
• Customer sentiment modeling from diverse sources.

6+ years with Bachelor’s degree; less for Master’s/Ph.D. Master’s or Ph.D. preferred in Machine Learning, Applied Math, Data Science, Computer Science, or related fields. Candidate must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I‑983 Training Plan endorsement for this position.

The listed annualized base pay range is $110,720 – $166,080. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short‑term or annual bonuses, long‑term incentives, and on‑the‑spot recognition.

Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age