Staff Data Scientist
Staff Data Scientist
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Salary Not Disclosed
1 Vacancy
Job Description
The role
The People Analytics team is moving beyond descriptive dashboards to deliver predictive and advanced analytical capabilities that drive talent and business outcomes. As a Staff People Data Scientist you will design build and productionize models and analyses (e.g. attrition risk headcount forecasts mobility quality of hire and etc) that inform decisions across the employee lifecycle. Youll be a handson builder and thought partner to People Analysts COEs (e.g. Talent Management Total Rewards TA) and crossfunctional stakeholders in Legal/Privacy Security Finance Product and Engineering.
Bonus: Experience with AI (e.g. LLMs NLP) is a plus and may be used to bring analyses to life via simple apps or assistants when it meaningfully improves access and adoption.
How This Role Elevates the People Team (and Company)
This role unlocks deeper predictive insights into employee behavior and program effectiveness enabling better talent decisions more equitable processes and measurable business impact (e.g. reduced turnover cost improved hiring efficiency better workforce allocation). Where appropriate we will scale insights through lightweight userfriendly tools (potentially AIassisted) that meet users where they are.
What youll do:
Build predictive capabilities across the employee lifecycle
- Develop validate and productionize models for attrition risk internal mobility recruiting funnel yield quality of hire performance and success trajectories engagement drivers and workforce/headcount forecasting.
- Stand up evaluation calibration monitoring and drift detection; own the model lifecycle from design through deployment and iteration.
Apply advanced analytical methods to business questions
- Design and implement segmentation decision trees survival/timetoevent time series hypothesis testing uplift modeling and anomaly detection to surface drivers and shape recommendations.
- When useful apply NLP to survey and case text to connect attitudinal and behavioral data.
- Translate complex analyses into clear narratives visuals and recommendations for executives and frontline stakeholders; create enablement that moves decisions and outcomes.
Advance the function
- Partner with Analysts/COEs to design A/B and quasiexperimental evaluations of People programs (e.g. onboarding recognition manager training) and translate results into clear actions.
- Serve as a technical subjectmatter expert mentoring analysts on statistical methods ML best practices experimentation and code quality.
- Bonus (optional): Package insights as internal tools (e.g. simple APIs Streamlit apps Tableau extensions) including AIassisted features where they add clear value.
Data foundations and operations
- Partner with People Data Engineering to define features and governed datasets in Snowflake
- Navigate the compliance and regulatory requirements for proper model and AI use across the People Team.
- Embed privacybydesign and fairness checks (bias detection/mitigation explain ability); align with Legal/Privacy and Security on data governance and appropriate use.
What youll need:
Education: Bachelors in Computer Science Statistics Economics Engineering Data Science or a quantitative field (Masters preferred).
Experience: 7 years in applied data science/ML (ideally in People Analytics Talent or adjacent domains) with a track record of shipping models/analyses that change decisions.
Technical depth:
- Strong ability to leverage a dimensional data model in Snowflake to build datasets for advanced analytics.
- Python (pandas scikitlearn statsmodels) SQL and Tableau for analytics & visualization or similar tools..
- Deep expertise in statistics and data science methods (e.g. linear/logistic regression causal inference A/B testing matching methods survival/time series).
Business influence: Ability to scope ambiguous problems balance speed and rigor and communicate clearly with technical and nontechnical partners; strong proactive ownership.
Nice to have:
- Peopledata fluency: Experience with HRIS/ATS/survey sources (e.g. Workday Greenhouse Qualtrics/Glint) text analytics on engagement/case data and KPI design (e.g. quality of hire timetofill internal mobility).
- Background in I/O Psychology or psychometrics; experience with pay equity fairness metrics and/or differential privacy.
- Building internal tools with Streamlit or lightweight web frameworks; AWS data/ML services.
- Experience mapping people outcomes to financial impact (productivity efficiency turnover cost).
- Experience with Snowflake dbt Airflow Git and model monitoring in production.
- AI/LLM experience (prompting RAG safety guardrails) to enhance discoverability and access to insights.
Required Experience:
Staff IC
Employment Type
Full-Time
