Skip to main content
G-P

Principal Data Scientist

RemoteIndia, United States only
Published
Role
Data Science
Experience
Principal
Salary not disclosed
Check eligibility

Open to IN, US only. Set where you work from to check your eligibility.

No BS summary

Principal Data Scientist with 5+ years experience in data science, data engineering, and analytics, with strong SQL and Python skills. Must have experience with Databricks or equivalent modern data platforms, LLM experience (fine-tuning, prompt engineering, embeddings, RAG, evaluation), and traditional ML depth. A product mindset and pipeline engineering skills are essential.

Core skills

LLMmachine learningdata engineering

Required skills

SQLPythonDatabricks/Snowflake/BigQueryprompt engineeringembeddingsRAGclassificationregressionclusteringNLPfeature engineering

Optional skills

dbtAirflowDagsterSpark

What you'll 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 they require

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

Benefits

  • competitive compensation and benefits
  • generous paid parental leave
  • flexible time off
  • spending accounts
  • medical insurance
  • dental insurance
  • vision insurance
  • sabbatical after 5 years

G-P

G-P is a SaaS-based Global Employment Platform™ focused on enabling global business and supporting remote-first teams.

SaaS
Salary not disclosed