Manager, People Analytics – Data Science

This is a fully remote position, open to applicants in United States.

📋 Description

• Collaborate with data engineers to design, construct, and sustain dependable data pipelines and analytical datasets.

• Create reusable data models, transformations, validation checks, documentation, and monitoring systems.

• Work alongside HR Tech, Enterprise Data Science, Data & Analytics, Finance, and other technical teams on data architecture, integrations, access, and data quality management.

• Convert business and People inquiries into precise data requirements, grains, dimensions, logic, refresh expectations, and ownership.

• Create and uphold metric contracts detailing definitions, calculation logic, sources, refresh cadence, interpretation, stewardship, and action paths.

• Enhance the reliability, transparency, privacy, and usability of people data.

• Manage the complete delivery of leader-facing people data products from discovery to launch, adoption, and iteration.

• Develop operational and executive dashboards that link people metrics to business and workforce outcomes.

• Design user-friendly self-service data experiences, along with documentation, enablement, and feedback mechanisms.

• Assess usage, trust, decision relevance, and adoption of data products.

• Perform targeted research and advanced analysis on workforce risks, attrition, capacity, workforce planning, manager effectiveness, performance, productivity, and AI-enabled work.

• Utilize exploratory analysis, statistical methods, experimentation, forecasting, segmentation, and predictive modeling.

• Interpret complex analyses into findings, limitations, implications, and actionable recommendations.

• Design analyses with a focus on validation, explainability, privacy protections, and bias awareness.

• Develop repeatable processes for research intake, hypothesis formation, analysis, peer review, storytelling, and follow-up.

• Connect analytical outcomes to decisions, interventions, and impact assessments.

• Foster relationships with People leaders, business leaders, Finance, HR Tech, Enterprise Data Science, and other collaborators.

• Shape and sustain an analytics roadmap.

• Set standards for data quality, versioning, testing, documentation, access, and responsible usage.

• Assist leaders and People partners in building confidence and fluency in people metrics and insights.

• Lead through influence and actively 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 discipline.

• Over 7 years of experience in data science, people analytics, analytics engineering, business intelligence, data engineering, or a similar field.

• Background in People Analytics, HR data, workforce planning, talent management, compensation, performance evaluation, or organizational research.

• Proven experience in building data pipelines, analytical datasets, data models, or other reusable analytics frameworks.

• Demonstrated capability in developing dashboards or self-service analytics products for business stakeholders.

• Experience in applying statistical analysis, experimentation, forecasting, segmentation, or predictive modeling to intricate business challenges.

• Ability to communicate analytical insights clearly to senior leaders and non-technical audiences.

• Proficient hands-on skills with SQL and Python or R.

• Familiarity with modern data pipelines, transformation, testing, and analytical workflows.

• Knowledge of 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.

• Capacity to differentiate between reporting, diagnostic, research, and modeling questions, selecting the most appropriate solution.

• Exercise strong judgment and discretion when managing confidential, sensitive, or personally identifiable People data.

• Comfortable utilizing AI and collaboration tools while adhering to responsible-use principles.

🏝️ Benefits

• Competitive compensation.

• Flexibility to work from anywhere in the United States for most positions.

• Paid time off, including vacation time, sick time, 9 paid Company holidays, and volunteer hours.

• Incentive bonus programs, including potential holiday bonuses, referral bonuses, and performance-based bonuses.

• Medical, dental, vision, life, and pet insurance.

• 401(k) retirement savings plan with company matching.

• Engaging work environment.

• Opportunities for promotion.

• Education assistance.

• Professional and personal development opportunities.

• Company recognition program.

• Health and wellbeing resources, including complimentary mental wellbeing therapy/coaching sessions, child and eldercare resources, and more.

• Potential for bonuses.