SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
EvolutionIQ is an AI-driven insurance technology company focused on improving outcomes for injured and disabled workers and reducing costs across the insurance industry. As a Staff Data Scientist on the Data Science & Insights team, you will serve as the analytics expert for internal and external stakeholders, using data and models to drive critical business decisions.
You will work closely with Engineering and Product teams to improve understanding of claims data and provide mission-critical insights that steer the company toward high-ROI initiatives. Your responsibilities include supporting leadership decision-making on product feature prioritization, designing and analyzing A/B tests and multi-arm experiments, uncovering new product research directions through exploratory data analysis, and creating data narratives that win clients and inform sales and marketing strategy.
Key deliverables include building and standardizing client-facing analysis and reporting, generating meta-analyses across clients to drive product and sales strategies, collaborating with the ML team to analyze modeling impact and debug data issues, and presenting results to both internal stakeholders and insurance industry clients. You will write efficient SQL queries, create reusable dashboards, maintain clean and maintainable code for reproducible analytics, perform code reviews, and drive cross-organizational projects.
This role requires 7+ years of data analysis and quantitative experience, preferably in ML and product environments, with at least 2 years mentoring junior analysts on business-critical projects. You should hold a Master's degree in statistics or equivalent quantitative field, with sophisticated knowledge of statistics, linear and non-parametric modeling, and advanced SQL. Proficiency in Python, pandas, Jupyter notebooks, and SQL-based analytics dashboards (DataStudio, Looker, or Tableau) is essential. Experience designing and analyzing A/B experiments with clear product recommendations is required.
