Data Scientist

Job Description Our client is seeking a Data Scientist to support the Group Insurance organization, with a focus on traditional machine learning use cases for medical and financial underwriting. This role is hands‑on and data‑driven, partnering closely with actuaries and technology teams to develop and support predictive models used in underwriting and pricing. Responsibilities

• Develop and apply traditional machine learning models (classification, survival models) for underwriting and pricing use cases
• Perform data extraction, cleaning, validation, and feature engineering on large datasets
• Analyze data quality issues and assemble usable analytical datasets from multiple sources
• Build and evaluate models using Python in an AWS cloud environment
• Partner with actuaries, IT, and ML engineering teams to support model deployment and testing
• Assist with troubleshooting, validation support, and research for failed test cases 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

• 3+ years of experience in data science, applied statistics, or machine learning
• Strong proficiency in Python (NumPy, Pandas, scikit‑learn, seaborn)
• Solid SQL skills for working with large databases
• Strong understanding of statistical and machine learning principles
• Experience building classification models; survival modeling experience strongly preferred
• Ability to communicate effectively with non‑data science stakeholders
• Master's degree (PhD a plus; Bachelor's considered with strong relevant experience)
• Experience working in AWS (e.g., S3, SageMaker notebooks)
• Exposure to insurance, underwriting, actuarial, or risk modeling domains
• Familiarity with software deployment or DevOps concepts (nice to have, not required)