Overview
Principal Data Scientist for an AI product (GIA) that applies data science, data engineering, and product analytics to ship models, measure impact, and translate insights into product decisions.
What you'll do
- Build and own data infrastructure including pipelines, warehousing, and ETL/ELT.
- Analyze product usage and user behavior to find patterns and meaningful segments.
- Build and train ML models including LLM-based systems; choose the right technique per problem.
- Define and track product-relevant metrics such as activation, retention, engagement, and PQLs.
- Run experiments including A/B tests, causal analysis, and cohort studies to measure impact.
- Turn data into product conviction by guiding decisions using insights beyond charts.
What you'll need
- 5+ years across data science, data engineering, and analytics.
- Strong SQL and Python for complex queries, data modeling, scripting, and analysis.
- Experience with Databricks or an equivalent data platform (Snowflake, BigQuery).
- LLM experience including fine-tuning, prompt engineering, embeddings, RAG, and evaluation.
- Traditional ML depth across classification, regression, clustering, NLP, and feature engineering.
- Pipeline engineering experience building reliable, scalable data pipelines.
- Clear communication skills presenting findings to non-technical stakeholders.
Read the full description and apply on the company’s own careers page.
