Principal Data Scientist
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Job Description
Principal Data Scientist building data infrastructure, analytics, and AI models for G-P’s AI-powered HR compliance platform. Turning product data into decisions for global employment teams.
Responsibilities:
- Build and own data infrastructure, including pipelines, warehousing, ETL/ELT, and data quality
- Analyze product usage and user behavior, identify patterns, segment users, and surface meaningful insights
- Build and ship LLM-based systems and traditional machine-learning models, including classification, clustering, NLP, and evaluation frameworks
- Define and track product and go-to-market metrics such as activation, retention, engagement, and PQLs
- Run A/B tests, causal analyses, and cohort studies to measure impact
- Turn data into product recommendations and explain what the team should do and why
- Evaluate data through real datasets, product-decision case studies, pipeline or model architecture exercises, and feature instrumentation exercises
Requirements:
- 5+ years across data science, data engineering, and analytics
- Strong SQL and Python skills
- Databricks or equivalent modern data platform experience, such as Snowflake or BigQuery
- LLM experience including fine-tuning, prompt engineering, embeddings, RAG, and evaluation
- Traditional machine learning depth in classification, regression, clustering, NLP, and feature engineering
- Product mindset connecting analysis to product decisions
- Experience building reliable, scalable data pipelines
- Ability to present findings clearly to non-technical stakeholders
- Preferred: experience at an early-stage startup or as a founding data hire
- Preferred: product analytics built from scratch, including instrumentation, event taxonomy, dashboards, and self-serve reporting
- Preferred: legal or HR domain experience
- Preferred: LLM evaluation and observability experience, including tracing, scoring, and drift detection
- Preferred: familiarity with dbt, Airflow/Dagster, Spark, or similar orchestration and transformation tools
Benefits:
- Competitive compensation
- Generous paid parental leave
- Flexible time off
- Spending accounts
- Medical insurance
- Dental insurance
- Vision insurance
- Sabbatical after 5 years
- Annual bonus for non-sales roles, dependent on individual and company performance
- Flexible work arrangements through remote-first teams
- Flexibility and resources to support employees
- Equal opportunity and reasonable accommodation support
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