• 7+ years of data analysis/quantitative experience, preferably within Machine Learning and Product environments
• At least 2 years experience in mentoring or tech-leading junior analysts and business-critical analytics projects
• Masters degree in statistics or equivalent quantitative field with strong focus on applied, data-driven solutions
• Sophisticated knowledge of statistics, linear & non-parametric modeling, and advanced SQL engineering experience
• Designed, implemented, and analyzed A/B or multi-arm experiments with clear recommendations for product direction & development
• Proficient in the use of Python, pandas, Jupyter notebooks, and SQL-based analytics dashboards (e.g., Google’s DataStudio / Looker or Tableau), and familiarity with standard statistical packages and visualization tools in Python
• Skilled data illustrator who makes market-ready graphs, slides, figures, and presentations
• Excellent communication, storytelling, and presentation skills
• Proven understanding of Product and Business analytics, fundamentals, and processes
• Proven ability to synthesize data insights into actionable recommendations
• Proven ability to handle large datasets via SQL and/or map-reduce analytics and data aggregation as needed

Desirable

• As a data-enthusiast on the team, you serve as the analytics expert for your internal stakeholders, using data & models to help them make better decisions
• You will work closely with the ML team and Product Managers to improve our team and clients' understanding of claims data; you work closely with business stakeholders to leverage internal data that demonstrates product ROI and give them mission-critical insights to steer the company in new high ROI directions
• Support the decision-making of EvolutionIQ’s leadership team in critical recommendations such as which product features we should build as they lead to highest projected ROI or measuring impact of existing product through sophisticated experimental design setups that best leverage the user feedback we have on challenging small data, high variance outcome problems
• Uncover new product research directions (hypothesis generation) through exploratory data analysis and hypothesis testing
• Create data insights to win clients by helping define and build the sales & marketing narrative
• Present results to internal stakeholders as well as our clients in the insurance industry
• Generate meta-analysis across clients to drive product & sales strategies
• Build, own, and standardize client-facing analysis and reporting on existing products across multiple clients and ROI dimensions
• Work closely with the ML team to analyze the impact of modeling results, debug data issues, and communicate findings to colleagues and clients
• Write efficient and reliable relational database queries, create re-usable dashboards, write design documents, write clean & maintainable code for reproducible analytics via CLI tools, perform code reviews, and maintain state-of-the-art engineering practices
• Continue to grow and learn in the data & analytics space, focusing on business problems that require making sense of large-scale structured and unstructured datasets
• Oversee the integration of cross-organizational projects, drive improvements and recommendations for your engineering and product counterparts, and define operational goals and objectives
• Provide direction and accomplish results for business leaders through solving hard measurement problems that impact business bottom line