Derived from job-description analysis by Serendipath's career intelligence engine.
This role involves leading the development of cutting-edge AI and machine learning solutions within The Hartford's Claims Data Science team, requiring a blend of technical expertise and business acumen to drive impactful changes in customer journey optimization and operational efficiency.
Original posting from The Hartford
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 Hartford seeks a Sr. Data Scientist to join the Claims Data Science team in developing machine learning and artificial intelligence solutions across a range of strategic initiatives.
The Claims & Operations Emerging Sciences team is focused on providing deep insights across the policy & claim lifecycles and making adjuster workflows more efficient by leveraging new technologies and analytical capabilities. The Emerging Sciences team builds and maintains integrated and interactive solutions with a toolkit including generative and agentic AI, natural language processing, and computer vision, as well as more traditional machine learning techniques. We deliver value by partnering closely with the business, IT, and other data science and engineering teams to help build a consistent approach to architecture and practices, while tailoring solutions to our customers' unique needs in accuracy, transparency, and scalability.
As a Sr. Data Scientist, you will participate in the entire model lifecycle, partnering with cross-functional business and technical partners to understand business strategies and design, develop, implement, and evolve modeling solutions. We use the latest technologies, machine learning methods, MLOps, and Agile delivery frameworks to build innovative and efficient solutions that maximize business value. This cutting edge and forward focused organization presents the opportunity for collaboration, self-organization within the team, influencing decision-making, and visibility as we focus on continuous business data delivery.
This role will have a Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week (Tuesday through Thursday).
Responsibilities
- Design, develop, and robustly evaluate LLM‑powered solutions, including prompt engineering, agent‑based workflows, and retrieval‑augmented generation (RAG), to achieve financial objectives, solve business problems, and identify long term opportunities that improve the customer journey
- Collaborate and partner with business stakeholders in a way that supports the vision and sustains a culture that treats analytics as a corporate asset
- Lead execution of machine learning and applied AI solutions, including traditional predictive models and generative AI use cases, in close collaboration with data science, engineering, and business partners
- Assist in identifying and assessing the value of new data sources and analytical techniques to ensure ongoing competitive advantage
- Contribute to successful implementation of strategies to achieve targeted business objectives
- Develop knowledge of The Hartford's formal and informal structures, business processes, and data sources in your area of expertise
- Remain current on research techniques and experiment with state‑of‑the‑art tools applicable to the team’s function (e.g., new modeling approaches, LLM capabilities)
- Provide economic, qualitative, and statistical support to ensure model outputs and AI‑driven recommendations are accurate, interpretable, and actionable for business decision‑making
- Learn/bring best practices to guide the direction of our Data Science and Data Engineering workflows
Qualifications
- 5+ years of relevant experience recommended
- Master’s or Ph.D., or equivalent experience, in Statistics, Applied Mathematics, Quantitative Economics, Actuarial Science, Data Science, Computer Science, or a similar analytical field
- Proficiency in statistical modeling, inference, experimentation, and building machine learning algorithms in Python
- Proficiency in SQL and navigating databases to extract relevant attributes
- Proficiency with Unix and Git and best practices in managing codebases
- Proficiency in the end‑to‑end analytical solution lifecycle, from requirements gathering to monitoring and production validation
- Experience building modeling solutions in cloud‑native environments, such as Google Cloud Platform, a plus
- Experience with software development and/or agent development a plus
- Able to communicate effectively with both technical and non‑technical teams
- Able to translate complex technical topics into business solutions and strategies, as well as turn business requirements into a technical solution
- Experience with leading project execution and driving change to core business processes through the innovative use of quantitative techniques
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 analy
Source: The Hartford careers