Replit
Engineering
DataScientist,People
“Data Scientist, People at Replit. Skills: Data Science, AI, LLMs, predictive modeling, causal inference, People Analytics. Build the analytical foundation to evaluate compensation competitiveness. Connect Ashby offer data, band position, acceptance rates, and market benchmarks into a live system that recommends specific adjustments”
Industry & Context.
Build the analytical foundation; Develop predictive models; Analyze organizational effectiveness; rigorous analysis
Ability to handle highly sensitive organizational and compensation data with discretion, In-office requirement of Monday, Wednesday, and Friday
What They're Looking For.
Must Have
Minimum 6 years of experience, Experience in People Analytics, compensation analytics, or workforce analytics, SQL and Python skills, Experience building predictive models and analytical frameworks for business decision-making, statistical foundation, including experimentation and causal inference, Experience working with large-scale operational or behavioral datasets, Demonstrated experience using AI and LLMs in analytics workflows, Ability to communicate complex insights clearly to executives and cross-functional partners, High ownership mindset and comfort operating in fast-moving environments, Ability to handle highly sensitive organizational and compensation data with discretion
Nice to Have
Experience at a high-growth or AI-native company, Experience building internal tools, agents, or automated workflows, Familiarity with organizational design, compensation, or talent management concepts, Experience with modern data stack tools (dbt, BigQuery, Snowflake, etc.), Experience with People systems such as Rippling, Ashby, Lattice, or Carta, Experience building on Replit, Experience with NLP or unstructured text analysis, Interest in the future of AI-native organizations and how AI changes the way companies operate
What You'll Do.
Build the analytical foundation to evaluate compensation competitiveness
Connect Ashby offer data
and market benchmarks into a live system that recommends specific adjustments
Develop predictive models and tooling that help managers and recruiters make better decisions faster
Design and deploy AI agents that draft first-pass recommendations for high-stakes People decisions
Build the recruiting analytics layer that connects sourcing channel to time-to-hire to first-year performance to tenure
Analyze organizational effectiveness
including spans and layers
and hiring efficiency
Partner with Finance to move from spreadsheets to live workforce model that accounts for attrition
and ramp time by function
Use LLMs and agentic workflows to analyze unstructured People data at scale
Replace recurring reporting cycles with always-on agents that surface insights to leaders when they need them
Support high-stakes organizational and talent decisions with rigorous analysis
How You'll Work.
Team & Collaboration
work across HR, Recruiting, Finance, and Data Engineering; partner closely with the People leadership team; Ability to communicate complex insights clearly to executives and cross-functional partners
Communication Scope
Ability to communicate complex insights clearly to executives and cross-functional partners
Applying for this Data Scientist, People role?
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