A remote Data & ML role at G-P.
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Original listing text, shown exactly as published by the company.
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 build the pipelines, run the analysis, train the models, and — most importantly — tell us what the data means for the product. Not dashboards for the sake of dashboards. Insights that change what we build next.
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
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.
Our ranges are established using objective market benchmarking data for this level of work. Final placement within the range is determined by gender-neutral criteria, including the candidate's relevant skills, experience, and specific qualifications for the role.
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.
G-P
Data & ML
38 open roles on Sydicom
G-P (Globalization Partners) is a global employment platform that provides Employer of Record (EOR) services. They enable companies to hire and manage international teams compliantly, without needing to establish local entities in various countries.
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