Senior Data Scientist & Engineer - Globalization Partners

About Us

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.

Our diverse, remote-first teams are essential to our success. We empower our Dream Team members with flexibility and resources, fostering an environment where innovation thrives and every contribution is valued and celebrated.

The work you do here will positively impact lives around the world. We stand by our promise: Opportunity Made Possible. In addition to competitive compensation and benefits, we invite you to join us in expanding your skills and helping to reshape the future of work.

At G-P, we assist organizations in building exceptional global teams in days, not months—streamlining the hiring, onboarding, and management process to unlock growth potential for all.

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. Built on over a decade of global employment and legal expertise and 100,000+ vetted articles, Gia analyzes and generates compliant documents and delivers the answers that HR leaders trust — reducing reliance on outside legal counsel and cutting compliance costs by up to 95%.

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 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.

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