Data Scientist

Job Description

Insight Global is looking for a mid-level Data Scientist. This person will sit remotely and responsibilities include: develop and implement data-driven solutions to improve underwriting performance. Experiment with various data sources and statistical modeling techniques. Automate statistical model monitoring and data analysis. Document and publish model monitoring reports utilizing markdown or similar software. Version, publish, and maintain model monitoring code utilizing SQL and python.

Prototype, test, and deploy machine learning models into production. Collaborate with stakeholders across the organization to identify and address key business and technical challenges. Work with ambiguous data to derive meaningful insights and create actionable recommendations.

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.

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• Minimum of 3-5 years of experience in an operations role within the insurance industry.
• 2-5 years of experience in one or more of the following areas:
  Risk Modeling, Geospatial Modeling, Statistical/ML Modeling.
• Proven experience building and deploying machine learning models in a production environment.
• Demonstrated ability to solve complex data problems with limited initial information.
• Experience working effectively in a collaborative environment with diverse stakeholders.
• Exceptional attention to detail and commitment to data quality.
• Hands-on experience with risk modeling techniques.
• Data engineering experience.
• Expertise in deploying machine learning models using industry-standard tools and platforms.
• Understanding of P&C insurance principles and practices.
• Ability to navigate and extract insights from ambiguous and unstructured data.
• Excellent communication and interpersonal skills for effective collaboration.
• A meticulous approach to data analysis and model validation.