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The Hartford

Applied AI Data Scientist

The Hartford

AI Applied Scientist responsible for building ML and GenAI models at The Hartford. Collaborating with cross-functional teams to drive AI solutions in underwriting and claims.

Posted 5/20/2026full-timeRemote • Connecticut, Illinois, North Carolina, Ohio • 🇺🇸 United StatesMid-LevelSenior💰 $90,160 - $135,240 per yearWebsite

Tech Stack

Tools & technologies
AWSAzureGoogle Cloud PlatformPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact
  • Build and optimize ML, deep learning, and GenAI models using modern frameworks (PyTorch, TensorFlow, scikit-learn)
  • Design and deliver RAG pipelines, hybrid retrieval systems, and vector-based search workflows
  • Develop Agentic AI solutions including tool orchestration, reasoning flows, and safe-execution strategies
  • Run structured experimentation using evaluation metrics (BERTScore, BLEURT, semantic similarity, retrieval precision/recall)
  • Integrate solutions into GCP (Vertex AI, Workbench, Vector Search) and AWS (SageMaker, Bedrock)
  • Build ingestion, enrichment, and semantic retrieval flows for high-quality knowledge and feature engineering
  • Partner with onshore and offshore DS/ML engineers to ensure quality, consistency, and shared technical patterns

Requirements

What you’ll need
  • 3–5+ years in Data Science, ML Engineering, Applied AI, or GenAI roles
  • Strong Python and SQL skills; experience with deep learning and ML libraries
  • Hands-on experience building RAG systems, vector search pipelines, and GenAI applications
  • Familiarity with modern LLM platforms (Vertex AI, OpenAI, Bedrock, Azure OpenAI)
  • Experience implementing evaluation methodologies for both ML and GenAI
  • Ability to translate ambiguous business problems into well-structured ML/GenAI solutions
  • Experience designing multi-step agent workflows and reasoning pipelines
  • Strong grounding in statistics, experiment design, and feature engineering
  • Ability to present complex concepts clearly to technical and business stakeholders
  • Experience partnering with SMEs to validate and refine AI outputs

Benefits

Comp & perks
  • Other rewards may include short-term or annual bonuses
  • long-term incentives
  • on-the-spot recognition

ATS Keywords

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Hard Skills & Tools
PythonSQLMLdeep learningGenAIRAG systemsvector search pipelinesevaluation methodologiesfeature engineeringstatistics
Soft Skills
problem-solvingcommunicationcollaborationpresentationcreativitycritical thinkingadaptabilityattention to detailorganizational skillsstakeholder engagement