Job Description We are seeking an experienced Data Scientist with a strong foundation in machine learning and a proven ability to translate research and experimentation into practical, production-ready solutions. This is an individual contributor role focused on building, deploying, and scaling ML models and intelligent automation solutions that directly support core business operations. You will collaborate with cross-functional teams—including product, engineering, and senior stakeholders—on strategic initiatives that bring next-generation ML capabilities into production. Key Responsibilities Design and implement machine learning solutions that automate workflows, enhance decision-making, and improve customer and employee experiences Apply ML techniques such as regression, classification, clustering, and ensemble methods (e.g., Random Forest, XGBoost) to structured and semi-structured data Build robust, scalable, and production-ready ML models that deliver measurable business impact Partner with data engineering and MLOps teams to ensure models are reliable, well-tested, and deployable at scale Translate statistical and machine learning research into practical applications across areas such as risk assessment, operational automation, and customer servicing Collaborate with product owners, engineers, and business stakeholders to define use cases, design solutions, and measure outcomes Contribute to reusable frameworks, tools, and best practices for ML development and deployment Follow model governance, documentation, testing, and validation standards 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.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements 2+ years hands-on Machine Learning experience building, deploying, and scaling production ML models using techniques such as regression, classification, clustering, and ensemble methods Strong Python skills with core ML/data libraries (scikit-learn, pandas, NumPy) Solid foundation in statistics, probability, and ML fundamentals Degree in a quantitative field (CS, Statistics, Engineering, Applied Math, or related) PhD Experience in insurance, financial services or related industries