[Hiring] Manager, People Analytics & Data Science @Mercury Insurance Services

Role Description

Mercury is building a connected, trusted people analytics capability that puts decision-ready data and insights in the hands of leaders when and where they need them. The Manager, People Analytics & Data Science will help build that capability from the data foundation through the leader experience. This role will build reliable data pipelines and analytical datasets, establish trusted metric definitions, and deliver robust dashboards that enable self-service people data for Mercury leaders. The role will also conduct targeted research and advanced analysis—including predictive and AI-enabled methods where appropriate—to surface new insights on workforce risks, capacity, performance, productivity, and other priorities. The successful candidate will combine technical depth with strong business judgment.

Responsibilities

• Data foundation and analytics engineering
  • Partner with data engineers to design, build, and maintain reliable data pipelines and analytical datasets.
  • Develop reusable data models, transformations, validation checks, documentation, and monitoring.
  • Partner with HR Tech, Enterprise Data Science, Data & Analytics, Finance, and other technical teams.
  • Translate business and People questions into clear data requirements.
  • Establish and maintain metric contracts that document definitions, calculation logic, sources, and action paths.
  • Improve the reliability, transparency, privacy, and usability of people data.
• Dashboards and self-service people data
  • Own the end-to-end delivery of leader-facing people data products.
  • Build robust operational and executive dashboards that connect people metrics to business outcomes.
  • Deliver focused dashboard experiences that help leaders answer key questions.
  • Design for self-service by developing intuitive personas and access patterns.
  • Embed relevant people insights into existing executive reporting.
  • Measure usage, trust, decision relevance, and adoption.
• Research, advanced analytics, and predictive insight
  • Conduct targeted research and analysis on prioritized questions.
  • Apply exploratory analysis, statistical methods, and predictive modeling.
  • Translate complex analysis into clear findings and recommendations.
  • Design analyses with appropriate validation and privacy protections.
  • Develop repeatable approaches for research intake and analysis.
  • Partner with stakeholders to connect analytical findings to decisions.
• Partnership and capability building
  • Build trusted relationships with People leaders and other partners.
  • Shape and maintain an analytics roadmap.
  • Establish practical standards for data quality and responsible use of people data.
  • Help leaders and People partners build confidence in using people metrics.
  • Lead through influence and contribute to a high-performing team.

Qualifications

• Bachelor’s degree in data science, statistics, computer science, mathematics, engineering, economics, business analytics, or a related field.
• 7+ years of experience in data science, people analytics, analytics engineering, business intelligence, or data engineering.
• Experience with People Analytics, HR data, workforce planning, talent, compensation, performance, or organizational research.
• Demonstrated experience building data pipelines and analytical datasets.
• Demonstrated experience developing dashboards or self-service analytics products.
• Demonstrated experience applying statistical analysis and predictive modeling.
• Strong hands-on skills with SQL and Python or R.
• Experience with data modeling, BI tools, and cloud data platforms.
• Strong foundation in statistics and model evaluation.

Requirements

• Able to distinguish between a reporting need, a diagnostic question, and a research or modeling question.
• Product-minded and user-centered.
• Strong storyteller who can make complex analysis clear and actionable.
• Highly collaborative and comfortable working across teams.
• Strong judgment when handling confidential data.
• Comfortable using AI and collaboration tools responsibly.
• Able to build in ambiguity and continuously improve work quality.

Benefits

• Competitive compensation.
• Flexibility to work from anywhere in the United States for most positions.
• Paid time off (vacation time, sick time, 9 paid Company holidays, volunteer hours).
• Incentive bonus programs.
• Medical, dental, vision, life, and pet insurance.
• 401 (k) retirement savings plan with company match.
• Engaging work environment.
• Promotional opportunities.
• Education assistance and professional development opportunities.
• Health and wellbeing resources, including free mental wellbeing therapy/coaching sessions.