Senior Data Scientist & Engineer - G-P

About G-P

Our leading SaaS-based Global Employment Platform™ enables clients to expand into over 180 countries quickly and efficiently, without the complexities of establishing local entities. At G-P, we’re dedicated to breaking down barriers to global business and creating opportunities for everyone, everywhere.

G-P helps organizations build global teams in minutes, not months. As part of this mission, we’ve created an indispensable AI agent for HR leaders, G-P Gia™. Gia is our AI-powered global HR agent that provides HR compliance guidance instantly, analyzing and generating compliant documents and delivering answers that HR leaders trust.

About The Position

We’re building GIA — AI for General Counsel, in-house legal teams, and HR teams. GIA is a startup that demands extreme ownership, relentless execution, and zero tolerance for waiting on someone else to make the call. This role sits at the intersection of data science, data engineering, and product analytics. You will build the pipelines, run the analysis, train the models, and — most importantly — tell us what the data means for the product.

What You Will Do

• Build and own data infrastructure: Pipelines, warehousing, ETL/ELT, data quality; make sure the foundation is solid.
• Analyze product usage and user behavior: Identify patterns, segment users, surface what matters from the noise; think like a product person, not just a data person.
• Build models that ship: LLM-based systems, traditional ML (classification, clustering, NLP), evaluation frameworks; whatever the problem needs.
• Define and track the metrics that matter: Activation, retention, engagement, PQLs; connect data to product and GTM decisions.
• Run experiments and measure impact: A/B tests, causal analysis, cohort studies; rigorous but fast.
• Turn data into product conviction: You don’t just hand off charts, you tell the team what to do and why.

What We Are Looking For

Minimum Requirements

• 5+ years across data science, data engineering, and analytics — you do all three, not just one.
• Strong SQL and Python skills — complex queries, data modeling, scripting, analysis.
• Databricks or equivalent modern data platform experience (Snowflake, BigQuery).
• LLM experience — fine-tuning, prompt engineering, embeddings, RAG, evaluation (not just API calls).
• Traditional ML depth — classification, regression, clustering, NLP, feature engineering.
• Product mindset — filter signal from noise, understand user behavior, and connect analysis to product decisions.
• Pipeline engineering — build reliable, scalable data pipelines, not notebooks that break in production.
• Clear communicator — present findings to non-technical stakeholders with clarity and conviction.

Preferred Qualifications

• Experience at an early-stage startup or as a founding data hire.
• Built product analytics from scratch — instrumentation, event taxonomy, dashboards, self-serve reporting.
• Legal or HR domain experience.
• Experience with LLM evaluation and observability (tracing, scoring, drift detection).
• Familiarity with dbt, Airflow/Dagster, Spark, or similar orchestration and transformation tools.

How We Evaluate

• Give you a real dataset and ask what you’d do with it — we want product thinking, not just technical chops.
• Walk us through a time your analysis changed a product decision.
• Design a data pipeline or model architecture on the whiteboard.
• Show us how you’d instrument and measure a new feature from scratch.

Benefits

• Competitive compensation and annual performance bonus.
• Generous paid parental leave.
• Flexible time off.
• Spending accounts.
• Medical, dental, and vision insurance.
• Sabbatical after 5 years.