{"id":2749862,"url":"https://alion.io/job/mercury-insurance-manager-people-analytics-data-science","title":"Manager, People Analytics & Data Science","company":{"id":8014,"name":"Mercury Insurance","domain":"mercuryinsurance.com","url":"https://alion.io/company/mercury-insurance","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"iCIMS","truth_index":null},"role":"Analytics","role_family":"Analytics","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":128136,"max":252194,"currency":"USD","period":"year","gross":null,"usd_annual":252194},"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Python","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-16T23:41:21Z","employer_posted_date":"2026-10-16","last_verified_at":"2026-11-02T08:56:27Z","board_verified":true,"closed_at":null,"days_open":16,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":16},"description":"Overview\nPosition Summary:\nMercury 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.\nThis 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.\nThe successful candidate will combine technical depth with strong business judgment. They will be able to move from a business question to a data model, from a data model to a clear dashboard, and from an observed pattern to a well-supported recommendation. This is a builder role for someone who wants to make people data easier to trust, easier to use, and more useful in the flow of business decisions.\nGeo-Salary Information\n An in-person interview may be required during the hiring process\nState specific pay scales for this role are as follows:$128,136 to $252,194 (NJ, NY, WA, HI, AK, MD, CT, RI, MA)\n$116,487 to $229,267 (NV, OR, AZ, CO, WY, TX, ND, MN, MO, IL, WI, FL, GA, MI, OH, VA, PA, DE, VT, NH, ME)\n$104,839 to $206,340 (UT, ID, MT, NM, SD, NE, KS, OK, IA, AR, LA, MS, AL, TN, KY, IN, SC, NC, WV)\nIn CA: Typical hiring range is $171,148 to $209,181\nThe expected base salary for this position will vary depending on a number of factors, including relevant experience, skills and location.\nResponsibilities\nData foundation and analytics engineering\nPartner with data engineers to design, build, and maintain reliable data pipelines and analytical datasets that bring together people, organizational, operational, and business data from relevant sources.\nDevelop reusable data models, transformations, validation checks, documentation, and monitoring that support accurate and repeatable analysis.\nPartner with HR Tech, Enterprise Data Science, Data & Analytics, Finance, and other technical teams on source systems, data architecture, integrations, access, and data quality.\nTranslate business and People questions into clear data requirements, grains, dimensions, logic, refresh expectations, and ownership.\nEstablish and maintain metric contracts that document definitions, calculation logic, sources, refresh cadence, interpretation, stewardship, and action path.\nImprove the reliability, transparency, privacy, and usability of people data as Mercury evolves its HRIS and broader data ecosystem.\nDashboards and self-service people data\nOwn the end-to-end delivery of leader-facing people data products, from discovery and prioritization through launch, adoption, and iteration.\nBuild robust operational and executive dashboards that connect people metrics to business and workforce outcomes.\nDeliver focused dashboard experiences that help leaders answer what changed, what may be contributing, and what action to take next.\nDesign for self-service by developing intuitive personas, access patterns, definitions, documentation, enablement, and feedback loops.\nEmbed relevant people insights into existing executive reporting and operating rhythms wherever possible rather than creating disconnected destinations.\nMeasure usage, trust, decision relevance, and adoption; use feedback and evidence to expand, refine, or retire products.\nResearch, advanced analytics, and predictive insight\nConduct targeted research and analysis on prioritized questions such as attrition risk, critical-role readiness, capacity constraints, workforce planning, manager effectiveness, performance, productivity, and AI-enabled work.\nApply exploratory analysis, statistical methods, experimentation, forecasting, segmentation, and predictive modeling as appropriate to the question and data quality.\nTranslate complex analysis into clear findings, limitations, implications, and recommendations for People and business leaders.\nDesign analyses with appropriate validation, explainability, privacy protections, and bias-awareness; treat models as decision support, not a substitute for accountable human judgment.\nDevelop repeatable approaches for research intake, hypothesis formation, analysis, peer review, storytelling, and follow-through.\nPartner with stakeholders to connect analytical findings to decisions, interventions, and measures of impact.\nPartnership and capability building\nBuild trusted relationships with People leaders, business leaders, Finance, HR Tech, Enterprise Data Science, and other partners.\nShape and maintain an analytics roadmap that balances foundational data work, self-service products, and targeted research.\nEstablish practical standards for data quality, versioning, testing, documentation, access, and responsible use of people data.\nHelp leaders and People partners build confidence and fluency in using people metrics and insights.\nLead through influence and contribute to a high-performing, collaborative People Ops, Tech & Analytics team.\nWhat success looks like\nLeaders can access trusted people metrics in the tools and business rhythms where decisions already happen.\nCore dashboards are clear, adopted, well-governed, and connected to meaningful business questions.\nData pipelines, metric definitions, and analytical products are reliable enough to support recurring decisions-not just one-time requests.\nTargeted research produces new, decision-relevant insight on priority workforce questions.\nThe team has a scalable roadmap for expanding self-service, predictive analysis, and future HRIS-enabled analytics.\nQualifications\nEducation\nBachelor’s degree in data science, statistics, computer science, mathematics, engineering, economics, business analytics, or a related field\nExperience\n7+ years of experience in data science, people analytics, analytics engineering, business intelligence, data engineering, or a related field.\nExperience with People Analytics, HR data, workforce planning, talent, compensation, performance, or organizational research.\nDemonstrated experience building data pipelines, analytical datasets, data models, or other reusable analytics infrastructure.\nDemonstrated experience developing dashboards or self-service analytics products for business stakeholders.\nDemonstrated experience applying statistical analysis, experimentation, forecasting, segmentation, or predictive modeling to complex business questions.\nDemonstrated ability to communicate analytical findings clearly to senior leaders and non-technical audiences.\nStrong hands-on skills with SQL and Python or R, plus experience with modern data pipelines, transformation, testing, and analytical workflows.\nExperience with data modeling, semantic layers, BI tools, cloud data platforms, version control, and production-quality documentation.\nStrong foundation in statistics, experimental design, causal reasoning, predictive modeling, and model evaluation.\nKnowledge and Skills:\nAble to distinguish between a reporting need, a diagnostic question, and a research or modeling question-and choose an appropriately rigorous solution.\nProduct-minded and user-centered: starts with the decision and designs the data experience around the user.\nStrong storyteller who can make complex analysis clear, precise, and actionable without overstating certainty.\nHighly collaborative, curious, pragmatic, and comfortable working across business and technical teams.\nStrong judgment and discretion when handling confidential, sensitive, or personally identifiable People data.\nComfortable using AI and collaboration tools to improve productivity while applying responsible-use principles.\nAble to build in ambiguity, establish standards without over-engineering, and continuously improve the quality of the work.\nAbout the Company\nWhy choose a career at Mercury?\nAt Mercury, we have been guided by our purpose to help people reduce risk and overcome unexpected events for more than 60 years. We are one team with a common goal to help others. Everyone needs insurance and we can’t imagine a world without it.\nOur team will encourage you to grow, make time to have fun, and work together to make great things happen. We embrace the strengths and values of each team member. We believe in having diverse perspectives where everyone is included, to serve customers from all walks of life.\nWe care about our people, and we mean it. We reward our talented professionals with a competitive salary, bonus potential, and a variety of benefits to help our team members reach their health, retirement, and professional goals.\nLearn more about us here: https://www.mercuryinsurance.com/about/careers\nPerks and Benefits\nWe offer many great benefits, including:\nCompetitive compensation\nFlexibility to work from anywhere in the United States for most positions\nPaid time off (vacation time, sick time, 9 paid Company holidays, volunteer hours)\nIncentive bonus programs (potential for holiday bonus, referral bonus, and performance-based bonus)\nMedical, dental, vision, life, and pet insurance\n401 (k) retirement savings plan with company match\nEngaging work environment\nPromotional opportunities\nEducation assistance\nProfessional and personal development opportunities\nCompany recognition program\nHealth and wellbeing resources, including free mental wellbeing therapy/coaching sessions, child and eldercare resources, and more\nMercury Insurance is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by federal, state, or local law.\nMercury is committed to working with and providing reasonable accommodations for qualified individuals with disabilities who need assistance with the application and/or employment consideration process. If you require an accommodation, you may contact us by sending an e-mail to . Please include your name, contact information, and a description of your requested accommodation in your message.\nPay Range\nUSD $128,136.00 - USD $252,194.00 /Yr.","description_format":"text","description_chars":10397,"description_truncated":false,"requirements":{"experience_years_min":7,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Education assistance","Retirement plans"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"},{"name":"Kentucky","iso":null,"kind":"city"},{"name":"Iowa","iso":null,"kind":"city"},{"name":"Florida","iso":null,"kind":"city"},{"name":"Wyoming","iso":null,"kind":"city"},{"name":"Texas","iso":null,"kind":"city"},{"name":"Virginia","iso":null,"kind":"city"},{"name":"New 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