Data Science Analyst at TransUnion focused on data insights in analytics initiatives. Requires a bachelor's degree and significant experience with technologies like SQL, R, and Tableau.
About the role
- Senior Data Scientist developing ML and AI solutions for The Hartford's Claims Data Science team. Collaborating to improve customer journey and drive efficiency in operations.
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
Requirements
- 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.
Benefits
- health insurance
- 401(k) matching
- Flexible work hours
- Paid time off
- Remote work options
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