Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

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About the job

Solve challenging data problems: Investigate complex regulatory data requests, identify relevant data sources, and perform the analysis needed to deliver accurate, complete, and defensible responses. Become a trusted data expert: Develop a deep understanding of our insurance products, underwriting data, and business processes, helping partners navigate complex data questions. Collaborate to deliver results: Work closely with regulatory, compliance, product, underwriting, and technology teams to understand requirements, resolve data challenges, and ensure responses meet business needs. Improve how we work: Identify recurring challenges and opportunities to simplify, standardize, and expedite the process of responding to regulatory requests. Build reusable knowledge: Document data sources, business logic, and prior analyses to make future requests easier to understand and fulfill. Drive visibility and accountability: Develop and maintain reporting that provides senior leadership with visibility into regulatory request status, progress, and emerging challenges, highlighting risks and issues that may require escalation or leadership support. Experience: 5+ years in data analytics or a related data solutions role, including coding for data management, data warehousing, or other data environments. Tooling: Comfortable across the broader data and analytics toolset used for the role (e.g., Snowflake, SAS Viya, SQL, GitHub), with the ability to use AI-assisted tools (e.g., GPT/Copilot/Claude) to improve productivity. Project management: Demonstrated experience leading projects from scoping through delivery and reporting on progress and challenges. Analytical mind: Candidate must be analytical and curious, with the ability to read ambiguous regulatory guidance, ask the right questions, and translate vague instructions into precise data requirements and testable rules. Leadership & autonomy: Proven ability to lead work cross-functionally and influence with limited guidance. AI: experience applying generative AI tools (e.g., Claude, ChatGPT) to data analysis, documentation, or workflow automation. Strong written and oral communication skills required. Bachelor`s Degree in Computer Science, Computer Engineering, or related discipline preferred. Master`s in same or related disciplines strongly preferred. 5-7 years' experience using SQL and/or Python for data analysis and reporting in data warehouse or similar data environments; experience with Snowflake and SAS is a plus. 5-7 years of experience in data research and process automation, with strong documentation skills.