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Manager, People Analytics – Data Science

🕒 October 17

🇺🇸 United States – Remote

💵 $128.1k - $252.2k / year

⏰ Full Time

🟠 Senior

🔴 Lead

📉 Data Analyst

Where this job comes from

Posted on Mercury Insurance's careers page, not through a job board

First seen by Remote Rocketship October 17

Still open on Mercury Insurance's site. Checked 0 minutes ago.

Logo of Mercury Insurance

Mercury Insurance

5001 - 10000 employees

Founded 1962

🚘 Automotive

💼 Consulting

📦 Logistics

Automotive • Consulting • Logistics

Mercury Insurance is a leading provider of insurance products, focusing on protecting individuals and their assets with a commitment to privacy and customer service. The company operates through independent agents and offers a range of insurance services including auto, home, and other personal insurance products. Mercury Insurance prioritizes the security of personal information and compliance with privacy laws, ensuring that customer data is handled with care and only shared when necessary for account servicing or as legally required.

📋 Description

• 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 on 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 covering definitions, calculation logic, sources, refresh cadence, interpretation, stewardship, and action paths • Improve the reliability, transparency, privacy, and usability of people data • Own end-to-end delivery of leader-facing people data products from discovery through launch, adoption, and iteration • Build operational and executive dashboards connecting people metrics to business and workforce outcomes • Design intuitive self-service data experiences, documentation, enablement, and feedback loops • Measure usage, trust, decision relevance, and adoption of data products • Conduct targeted research and advanced analysis on workforce risks, attrition, capacity, workforce planning, manager effectiveness, performance, productivity, and AI-enabled work • Apply exploratory analysis, statistical methods, experimentation, forecasting, segmentation, and predictive modeling • Translate complex analysis into findings, limitations, implications, and recommendations • Design analyses with validation, explainability, privacy protections, and bias awareness • Develop repeatable approaches for research intake, hypothesis formation, analysis, peer review, storytelling, and follow-through • Connect analytical findings to decisions, interventions, and impact measures • Build relationships with People leaders, business leaders, Finance, HR Tech, Enterprise Data Science, and other partners • Shape and maintain an analytics roadmap • Establish standards for data quality, versioning, testing, documentation, access, and responsible use • Help leaders and People partners build confidence and fluency in people metrics and insights • Lead through influence and contribute to a collaborative People Ops, Tech & Analytics team

🎯 Requirements

• 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, data engineering, or a related field • Experience with People Analytics, HR data, workforce planning, talent, compensation, performance, or organizational research • Demonstrated experience building data pipelines, analytical datasets, data models, or other reusable analytics infrastructure • Demonstrated experience developing dashboards or self-service analytics products for business stakeholders • Demonstrated experience applying statistical analysis, experimentation, forecasting, segmentation, or predictive modeling to complex business questions • Demonstrated ability to communicate analytical findings clearly to senior leaders and non-technical audiences • Strong hands-on skills with SQL and Python or R • Experience with modern data pipelines, transformation, testing, and analytical workflows • Experience with data modeling, semantic layers, BI tools, cloud data platforms, version control, and production-quality documentation • Strong foundation in statistics, experimental design, causal reasoning, predictive modeling, and model evaluation • Ability to distinguish between reporting, diagnostic, research, and modeling questions and select an appropriately rigorous solution • Strong judgment and discretion when handling confidential, sensitive, or personally identifiable People data • Comfortable using AI and collaboration tools while applying responsible-use principles

🏖️ 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 (potential for holiday bonus, referral bonus, and performance-based bonus) • Medical, dental, vision, life, and pet insurance • 401 (k) retirement savings plan with company match • Engaging work environment • Promotional opportunities • Education assistance • Professional and personal development opportunities • Company recognition program • Health and wellbeing resources, including free mental wellbeing therapy/coaching sessions, child and eldercare resources, and more • Bonus potential

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