Data Scientist, B2B Generalist

This role will partner with leaders across GTM, Revenue, Product, Finance, RevOps, Strategy, and Data Science to answer questions tied to international strategy, monetization, product penetration, field deployment, customer opportunity, and organizational design. This is a founding-style opportunity within the broader GTM Data Science organization.

In this role, you will:

• Structure ambiguous B2B and go-to-market questions into clear operational plans, identifying the decision at stake, the evidence needed, and how insights will translate into action.
• Lead strategic deep dives across international expansion, monetization, product penetration, customer segmentation, field deployment, ecosystem dynamics, and organizational design.
• Analyze product usage, customer behavior, adoption patterns, sales and field activity, pipeline and revenue signals, and market context to identify the drivers of B2B growth.
• Partner closely with GTM, Revenue, Product, Finance, RevOps, Strategy, and Data Science leaders to turn analysis into prioritization decisions, field plays, investment choices, and operating cadences.
• Communicate complex findings to executives and cross-functional partners with crisp recommendations, transparent assumptions, and clear tradeoffs.
• Bring practical AI fluency to the work, using modern AI tools to accelerate analysis, synthesize evidence, improve workflows, and identify new ways data science can support business decision-making.
• Help define the operating model for an emerging B2B data science capability, including how the team frames problems, engages stakeholders, evaluates opportunities, and turns insights into GTM action.

You might thrive in this role if you have:

• Senior-level experience in a quantitative role such as Data Science, Product Analytics, Decision Science, Growth Analytics, Strategy Analytics, or a related field.
• Strong business judgment and a track record of translating ambiguous analytical work into decisions that business leaders can act on.
• Experience working on B2B, GTM or commercial strategy, monetization, product growth, or similarly complex business problems.
• Strong technical fluency with analytical tools such as SQL and Python, or equivalent experience using data to answer open-ended business questions.
• Ability to connect data across product, customer, sales, revenue, market, and operational contexts to form a coherent view of the business.
• Consulting-style problem solving: you can structure a broad question, identify the highest-leverage analysis, manage uncertainty, and communicate a practical recommendation.
• Excellent executive communication and cross-functional partnership. You can influence senior leaders, field teams, product partners, operators, and other data scientists with clear evidence and balanced judgment.
• Comfort operating in a high-ambiguity, fast-changing environment where the team, roadmap, and stakeholder model are still taking shape.
• Practical AI fluency and curiosity about how modern AI tools can improve analytical workflows, strategic synthesis, and decision support.
• Experience in strategy consulting followed by data science work in technology, or data science work within a consulting analytics practice, is a strong plus.
• An advanced degree is welcome but not required.