GEN AI Sr Data Scientist​/Data Scientist

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GEN AI Sr Data Scientist/Data Scientist Apply remote type 100% Remote locations Hartford, CT Chicago, IL Columbus, OH Charlotte, NC time type Full time posted on Posted 30+ Days Ago job requisition  R2520810 Sr Data Scientist - GD07AE
Data Scientist - GD08AE

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.

Step into the future with The Hartford as a Data Scientist / Sr Data Scientist, where Generative AI isn't just a buzzword— it's central to our strategy. Join a team that's pioneering AI-driven solutions in underwriting, claims processing, and customer service, transforming how we operate and make decisions. As part of our horizontal language-focused Gen AI team, you'll tackle advanced use cases and shape the development of Gen AI capabilities across the organization.

Here, your work will have a tangible impact, driving innovation and operational excellence with cutting-edge AI tools. If you're looking for a role where your expertise is not only valued but essential to our success, The Hartford is the place for you.

We are looking for a technically proficient GenAI data scientist with deep implementation experience in building and evaluating GenAI systems, and a proven ability to stay at the forefront tools and techniques in the evolving AI landscape.

This role can have a Hybrid or Remote work schedule. Candidates who live near one of our locations will have the expectation of working in an office 3 days a week (Tuesday through Thursday).

Responsibilities :

• Support The Hartford’s AI innovation strategy to identify and implement high-end use cases , ensuring alignment with business objectives and emerging industry trends.

• Support cutting-edge AI vision and roadmap for the enterprise to make The Hartford a leader in using AI for the insurance industry.

• P artner with stakeholders internal to the Data Science organization, Technology organization and business organization, aligning with business objectives and driving innovation to improve productivity and efficiency of underwriting and sales efforts.

• Design and build GenAI solutions for tasks such as summarization, question answering, search, data synthesis, etc.

• Rapidly prototype with cutting-edge t ools, such as Vertex
  
  AI / Google a gent development kit, Lang Chain / Lang Graph , RAG frameworks, Hugging Face , OpenAI APIs, etc.

• Research and recommend noval foundation model options, tools, and libraries to improve solutions in performance and reliability.

• Develop evaluation pipelines for generati ve outputs using a mix of automatic metrics, human feedback, and llm
  -as-a-judge methods.

• Collaborate with ML Ops to ensure best practice is followed for scalable training and deployment.

Qualifications :

• Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, Engineering or a related field .

• 3+ years of industry experience in machine learning or data science and with 1+ years focused on GenAI .

• Proven experience in GenAI tools such as Vertex AI/Google agent development kit, Lang Chain / Lang Graph , RAG frameworks, Hugging Face , OpenAI APIs, etc.

• Solid understanding of prompt engineering, retrieval-augmented generation (RAG) , agent workflow, and LLM evaluation.

• Proficiency in Python and ML frameworks such as PyTorch , Tensor Flow, etc.

• Experience with vector databases such as Chroma, Pinecone, etc. and cloud platforms such as GCP, AWS, Azure, etc.

• Strong analytical, problem solving and debugging skills.

• Excellent communication and collaboration skills, with the ability to explain complex technical concepts to non-technical stakeholders across the enterprise.
• 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.

Compensation

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could…