Data Scientist

Job Description We are seeking an experienced Data Scientist to join our clients Life Insurance Underwriting team. This role will support large-scale underwriting initiatives focused on mortality risk modeling and premium determination. The ideal candidate brings strong traditional data science experience, a solid foundation in statistical and machine learning techniques, and the ability to work independently in a production, business-facing environment. This is not a data engineering or GenAI-heavy role. The majority of the work will focus on classical machine learning and statistical modeling using structured health and insurance data. Key Responsibilities Develop, validate, and maintain machine learning and statistical models to support life insurance underwriting decisions Analyze and model health and demographic data to assess mortality risk and premium outcomes Translate underwriting and business requirements into analytical solutions Partner with underwriters, analysts, and stakeholders to interpret model outputs and findings Conduct exploratory data analysis, feature engineering, and model performance evaluation Document methodologies, assumptions, and results in a clear and structured manner Contribute to model lifecycle activities including monitoring and refinement Operate independently while collaborating effectively within a broader analytics team We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.

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https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements Strong experience in traditional data science and machine learning Proficiency in Python and SQL Hands-on experience with: ○ Regression models ○ Random Forest ○ Gradient boosting methods (e.g., XGBoost) Experience working in a Git/GitHub-based development environment Familiarity with standard data science workflows and best practices Masters or PhD in a Data Science related field Experience in insurance, life insurance underwriting, healthcare, or health data analytics Exposure to actuarial concepts or risk modeling Limited exposure to AI / GenAI tools (expected usage ~10-15%, not a core requirement)