Manager, People Analytics & Data Science
New
J
JobgetherPeople analytics
The position is remote within the United States.Full-TimeManager
SalarySalary: Compensation varies by state and depends on experience, skills, and location: California: typical hiring range of $171,148–$209,181 per year. New Jersey, New York, Washington, Hawaii, Alaska, Maryland, Connecticut, Rhode Island, and Massachusetts: $128,136–$252,194 per year. Nevada, Oregon, Arizona, Colorado, Wyoming, Texas, North Dakota, Minnesota, Missouri, Illinois, Wisconsin, Florida, Georgia, Michigan, Ohio, Virginia, Pennsylvania, Delaware, Vermont, New Hampshire, and Maine: $116,487–$229,267 per year. Utah, Idaho, Montana, New Mexico, South Dakota, Nebraska, Kansas, Oklahoma, Iowa, Arkansas, Louisiana, Mississippi, Alabama, Tennessee, Kentucky, Indiana, South Carolina, North Carolina, and West Virginia: $104,839–$206,340 per year.
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Job Details
- Experience
- At least 7 years of experience in data science, people analytics, analytics engineering, business intelligence, data engineering, or a related discipline.
- Required Skills
- PythonSQLBusiness IntelligenceData modelingR
Requirements
- Bachelor's degree in data science, statistics, computer science, mathematics, engineering, economics, business analytics, or a related field.
- At least 7 years of experience in data science, people analytics, analytics engineering, business intelligence, data engineering, or a related discipline.
- Experience with people analytics, HR data, workforce planning, talent management, compensation, performance, or organizational research.
- Demonstrated ability to build data pipelines, analytical datasets, data models, or reusable analytics infrastructure.
- Experience developing dashboards and self-service analytics products for business stakeholders.
- Experience applying statistical analysis, experimental design, forecasting, segmentation, or predictive modeling to complex business problems.
- Strong hands-on proficiency in SQL and Python or R.
- Experience with modern data pipelines, data transformation, testing, and analytical workflows.
- Knowledge of data modeling, semantic layers, business intelligence tools, cloud data platforms, version control, and production-quality documentation.
- Understanding of statistics, causal reasoning, experimental design, predictive modeling, and model evaluation.
- Ability to explain complex findings clearly and make evidence-based recommendations to senior leaders and non-technical audiences.
- Discretion in handling confidential, sensitive, and personally identifiable employee information.
Responsibilities
- Build and maintain reliable data pipelines and analytical datasets integrating workforce, organizational, operational, and business information.
- Develop reusable data models, transformations, validation checks, documentation, and monitoring.
- Establish trusted metric definitions and improve the reliability, transparency, privacy, and usability of people data.
- Lead workforce analytics products from requirements gathering and prioritization through launch, adoption, and continuous improvement.
- Build operational and executive dashboards and intuitive self-service analytics experiences.
- Investigate workforce topics including attrition, critical-role readiness, workforce capacity, manager effectiveness, performance, productivity, and AI-enabled work.
- Apply statistical analysis, experimentation, forecasting, segmentation, and predictive modeling to workforce questions.
- Translate analytical findings into recommendations, explaining limitations, implications, and uncertainty.
- Develop an analytics roadmap and practical standards for data quality, testing, documentation, access, and responsible use.
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