Manager, People Analytics – Data Science

🕒 6 dias atrás

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $128.136 - $252.194 / ano

⏰ Tempo Integral

🟠 Sênior

🔴 Especialista

📉 Analista de Dados

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Mercury Insurance

SiteLinkedInTodas as Vagas

5001 - 10000 funcionários

Fundada em 1962

🚘 Automotivo

💼 Consultoria

📦 Logística

Automotive • Consulting • Logistics

A Mercury Insurance é um provedor líder de produtos de seguro, focando em proteger indivíduos e seus bens com um compromisso com a privacidade e o atendimento ao cliente. A empresa opera através de agentes independentes e oferece uma variedade de serviços de seguros, incluindo seguros de automóveis, residenciais e outros produtos de seguro pessoal. A Mercury Insurance prioriza a segurança das informações pessoais e a conformidade com as leis de privacidade, garantindo que os dados dos clientes sejam manuseados com cuidado e compartilhados apenas quando necessário para o atendimento de contas ou conforme exigido por lei.

Descrição

• 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

🎯 Requisitos

• 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

🏖️ Benefícios

• 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