Data Scientist, People & Workforce Analytics

Ivy Rehab • Philadelphia, PA

23h • Remote

About The Position

Join Ivy Rehab’s dedicated team, where you are a valued teammate providing world-class care in physical therapy, occupational therapy, speech therapy, and applied behavior analysis (ABA) services. The company culture promotes authenticity, inclusion, growth, community, and a passion for exceptional patient care. Ivy Rehab Network is seeking a Data Scientist with a focus on People and Workforce Analytics to join their New Jersey/New York team. This role is for a technical innovator who will leverage Ivy’s data ecosystem to build predictive models and deploy cutting-edge AI tools, including LLMs and AI Agents, to transform how the company manages its 7000+ teammates. The goal is to improve the teammate experience, operational performance, and workforce efficiency. The Analytics & Insights department provides data-driven strategies across the organization. In this HR-focused role, the Data Scientist will optimize the Teammate Experience, solve complex workforce problems, drive actionable insights by querying the Snowflake Data Lake, lead full lifecycle People Analytics projects, deploy predictive solutions, and drive self-service AI by developing and implementing AI Agents and LLM-based tools. The role also involves scaling People Strategy by uncovering trends in recruitment, retention, and teammate engagement to inform executive-level strategy.

Requirements

• Master’s Degree in Data Science, Statistics, Economics, Industrial-Organizational Psychology, or a related field
• Demonstrated experience deploying machine learning models into production environments
• Experience with Python, R, and SQL, including libraries used for LLM orchestration or AI agent development
• Proficiency in automating data processing tasks through scripting and Snowflake/Snowpark
• 3+ years of experience querying data lakes (Snowflake preferred) and manipulating large datasets to perform advanced and predictive analytics
• Ability to present results using professional formatting and graphical representations that clearly communicate insights to non-technical business partners
• Demonstrated experience in data cleaning, feature engineering, and model diagnostics
• Ability to communicate technical findings to non-technical HR business partners effectively

Nice To Haves

• Ability to identify data irregularities, perform quality assurance checks, and present findings and proposed solutions to leadership
• Ability to work in a fast-paced environment while maintaining a positive attitude
• Flexible positive attitude: Hungry to solve problems and grow within the organization
• Self-motivated with the willingness to exceed expectations, learn and grow
• Excellent written and verbal communication and presentation skills
• Ability to prepare written analysis and summarize results using graphical representations and professional formatting
• Partner cross-functionally at all levels of the organization and effectively, both verbally and visually, communicate findings and insights to non-technical business partners
• Ability to work with end users and translate business requirements into technical requirements/solutions
• Outstanding time management skills and ability to multitask
• Self-starter, able to work with limited supervision
• Demonstrates curiosity and a creative approach to problem-solving
• Comfort and confidence in working within a rapidly developing data lake and warehouse environment
• Proficient in Microsoft Word, Excel, and PowerPoint

Responsibilities

• Optimize the Teammate Experience: Use data to improve recruitment, retention, and engagement
• Solve Complex Workforce Problems: Address challenges such as turnover prediction, compensation equity, and productivity
• Drive Actionable Insights: Query our Snowflake Data Lake to join large HR datasets (e.g., payroll, ATS, engagement surveys) to uncover trends
• Full Lifecycle Projects: Lead People Analytics projects from initial hypothesis to final executive presentation
• Deploy Predictive Solutions: Responsible for the end-to-end development, deployment, and maintenance of machine learning models in production environments to solve complex workforce problems
• Drive Self-Service AI: Develop and implement AI Agents and LLM-based tools that allow non-technical HR partners to query workforce data and receive actionable insights through natural language
• Scale People Strategy: By joining large datasets from our Snowflake Data Lake, uncover trends in recruitment, retention, and teammate engagement to inform executive-level strategy
• Advanced Modeling: Develop statistical models and machine learning pipelines to predict workforce trends, such as "likelihood to leave" or hiring success
• Hypothesis Testing: Perform rigorous testing on HR initiatives to determine their impact on teammate performance and satisfaction
• ML Engineering: Build and maintain machine learning pipelines that automate the delivery of critical business metrics and pattern recognition in large HR datasets
• AI Innovation: Identify and implement use cases for Generative AI, specifically developing agents that accelerate data cleaning and feature engineering
• Integration: Seamlessly integrate predictive outputs and AI-driven insights into Power BI dashboards to promote a culture of self-service analytics
• Diagnostic Analysis: Run model diagnostics (VIFs, correlation coefficients) to ensure the fairness and accuracy of people-related models
• Visualization & Reporting: Design Power BI dashboards that allow HR leadership to track critical metrics like headcount, diversity, and turnover in real-time
• Collaboration: Partner with HR stakeholders to translate business questions into technical requirements

Benefits

• Eligibility for full benefits package beginning within your first month of employment
• Generous PTO (Paid Time Off) plans
• Paid holidays
• Professional development tracks
• Continuing education
• Leadership development
• Residency cohorts
• Mentorship programs
• Many other resources

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 501-1,000 employees