M

Mercury Insurance

Auto and home insurance via agents

Manager – People Analytics & Data Science

Data Science +1Confirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • A bachelor's degree in data science, statistics, computer science, mathematics, engineering, economics, business analytics, or a related field is required.
  • At least 7 years of experience in data science, people analytics, analytics engineering, business intelligence, data engineering, or a related field is required.
  • Experience with people analytics, HR data, workforce planning, talent, compensation, performance, or organizational research is required.
  • Experience building data pipelines, analytical datasets, data models, or other reusable analytics infrastructure is required.
  • Experience developing dashboards or self-service analytics products for business stakeholders is required.
  • Experience applying statistical analysis, experimentation, forecasting, segmentation, or predictive modeling to complex business questions is required.
  • Ability to communicate analytical findings clearly to senior leaders and non-technical audiences is required.
  • Hands-on skills with SQL and Python or R, plus experience with modern data pipelines, transformation, testing, and analytical workflows, are required.
  • Experience with data modeling, semantic layers, business intelligence tools, cloud data platforms, version control, and production-quality documentation is required.
  • A strong foundation in statistics, experimental design, causal reasoning, predictive modeling, and model evaluation is required.
  • Ability to distinguish between reporting needs, diagnostic questions, and research or modeling questions and select an appropriately rigorous solution is required.
  • Ability to handle confidential, sensitive, or personally identifiable people data with strong judgment and discretion is required.
  • Comfort using artificial intelligence and collaboration tools to improve productivity while applying responsible-use principles is required.
  • Ability to build amid ambiguity, establish standards without over-engineering, and continuously improve work quality is required.

Responsibilities

  • Partner with data engineers to design, build, and maintain reliable data pipelines and analytical datasets that combine people, organizational, operational, and business data from relevant sources.
  • Develop reusable data models, transformations, validation checks, documentation, and monitoring to support accurate and repeatable analysis.
  • Partner with HR technology, Enterprise Data Science, Data & Analytics, Finance, and other technical teams on source systems, data architecture, integrations, access, and data quality.
  • Translate business and People questions into clear data requirements, grains, dimensions, logic, refresh expectations, and ownership.
  • Establish and maintain metric contracts documenting definitions, calculation logic, sources, refresh cadence, interpretation, stewardship, and action path.
  • Improve the reliability, transparency, privacy, and usability of people data as the HR information system and broader data ecosystem evolve.
  • Own end-to-end delivery of leader-facing people data products, from discovery and prioritization through launch, adoption, and iteration.
  • Build operational and executive dashboards connecting people metrics to business and workforce outcomes.
  • Deliver focused dashboard experiences that help leaders understand what changed, what may contribute, and what action to take next.
  • Design for self-service by developing intuitive personas, access patterns, definitions, documentation, enablement, and feedback loops.
  • Embed relevant people insights into existing executive reporting and operating rhythms where possible.
  • Measure usage, trust, decision relevance, and adoption; use feedback and evidence to expand, refine, or retire products.
  • Conduct targeted research and analysis on priorities such as attrition risk, critical-role readiness, capacity constraints, workforce planning, manager effectiveness, performance, productivity, and AI-enabled work.
  • Apply exploratory analysis, statistical methods, experimentation, forecasting, segmentation, and predictive modeling as appropriate to the question and data quality.
  • Translate complex analysis into clear findings, limitations, implications, and recommendations for People and business leaders.
  • Design analyses with appropriate validation, explainability, privacy protections, and bias awareness, treating models as decision support rather than substitutes for accountable human judgment.
  • Develop repeatable approaches for research intake, hypothesis formation, analysis, peer review, storytelling, and follow-through.
  • Partner with stakeholders to connect analytical findings to decisions, interventions, and impact measures.
  • Build trusted relationships with People leaders, business leaders, Finance, HR technology, Enterprise Data Science, and other partners.
  • Shape and maintain an analytics roadmap balancing foundational data work, self-service products, and targeted research.
  • Establish practical standards for data quality, versioning, testing, documentation, access, and responsible use of people data.
  • Help leaders and People partners build confidence and fluency in using people metrics and insights.
  • Lead through influence and contribute to a high-performing, collaborative People Ops, Tech & Analytics team.

About the Company

Mercury Insurance

Auto and home insurance via agents

Mercury Insurance provides auto, home, condo, renter, and business insurance through a network of local independent agents. Its products are selected with guidance from agents and include options like mechanical protection; pricing is based on multiple factors rather than a single rate. Mercury differentiates itself with an independent agency model coupled with factor-based pricing and a long-standing asset base, supporting growth across several states. Its goal is to help people reduce risk and overcome unexpected events by offering reliable coverage and timely assistance through its agent network.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Brea, CA
Founded
1962

Recently Posted Jobs

Explore more opportunities at Mercury Insurance

See more jobs