The People Analytics team is looking to move beyond descriptive dashboards to deliver predictive and advanced analytical capabilities that drive talent and business outcomes for SoFi.
Requirements
- Strong ability to leverage a dimensional data model in Snowflake to build datasets for advanced analytics.
- Python (pandas, scikit‑learn, 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).
- 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.
- 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, time‑to‑fill, internal mobility).
- Building internal tools with Streamlit or lightweight web frameworks; AWS data/ML services.
Responsibilities
- 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.
- Design and implement segmentation, decision trees, survival/time‑to‑event, 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.
- Partner with Analysts/COEs to design A/B and quasi‑experimental evaluations of People programs (e.g., onboarding, recognition, manager training) and translate results into clear actions.
- Serve as a technical subject‑matter expert, mentoring analysts on statistical methods, ML best practices, experimentation, and code quality.
- Partner with People Data Engineering to define features and governed datasets in Snowflake
Other
- 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.
- Ability to scope ambiguous problems, balance speed and rigor, and communicate clearly with technical and non‑technical partners; strong, proactive ownership.
- Background in I/O Psychology or psychometrics; experience with pay equity, fairness metrics, and/or differential privacy.
- Experience mapping people outcomes to financial impact (productivity, efficiency, turnover cost).
- Master's preferred.
