G-P - Senior Data Scientist & Engineer
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Requirements
• 5+ years across data science, data engineering, and analytics — you do all three, not just one • Strong SQL and Python — complex queries, data modeling, scripting, analysis; this is your daily toolkit • 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; you pick the right tool for the problem • Product mindset — you filter signal from noise, understand user behavior, and connect analysis to product decisions • Pipeline engineering — you build reliable, scalable data pipelines, not notebooks that break in production • Clear communicator — you present findings to non-technical stakeholders with clarity and conviction • 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) • Familiar 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 • Interested? Reach out with an example of an insight you uncovered that changed what a team built. • Actual compensation for this position may vary and will depend on multiple factors such as relevant qualifications, experience, education, and geographic location. For Full-Time Regular Employees, this position is also eligible for additional compensation as follows: • Sales Roles: This position is eligible for a commission structure in addition to base salary. • Non-Sales Roles: This position is eligible for an annual bonus which is paid dependent on various factors, including and without limitation, individual and company performance in addition to base salary.
Responsibilities
• Build and own data infrastructure — pipelines, warehousing, ETL/ELT, data quality; make sure the foundation is solid • Build and own data infrastructure • 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 • Analyze product usage and user behavior • Build models that ship — LLM-based systems, traditional ML (classification, clustering, NLP), evaluation frameworks; whatever the problem needs • Build models that ship • Define and track the metrics that matter — activation, retention, engagement, PQLs; connect data to product and GTM decisions • Define and track the metrics that matter • Run experiments and measure impact — A/B tests, causal analysis, cohort studies; rigorous but fast • Run experiments and measure impact • Turn data into product conviction — you don’t just hand off charts, you tell the team what to do and why • Turn data into product conviction
Benefits
• G-P values its employees and offers excellent benefits and perks including generous paid parental leave, flexible time off, spending accounts, medical insurance, dental insurance, vision insurance, sabbatical after 5 years and more. • Individuals residing, or applying to work, in the United States: California or Philadelphia, Pennsylvania, please review the following additional information:G-P will consider qualified applicants with arrest or conviction records in accordance with the California Fair Chance Act, Los Angeles City Fair Chance Act Ordinance, Los Angeles County Fair Chance Act Ordinance, and San Francisco Fair Chance Act Ordinance. Los Angeles applicants can review additional information regarding the Los Angeles City Fair Chance Act here: Fair Chance Initiative for Hiring Ordinance, and Philadelphia applicants can review information pertaining to Philadelphia’s Fair Criminal Record Screening Standards Ordinance here: Fair Chance Poster. Any consideration of a candidate’s background check with arrest or conviction records will include an individualized assessment based on the factors required by applicable law, including the candidate’s specific record and the duties and requirements of the specific job. • United States: California or Philadelphia • Pennsylvania, • G-P. Global Made Possible.
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