Sr. Data Scientist

As a Senior Data Scientist, you’ll own the full lifecycle of intelligence solutions, from problem definition and analysis through model development, stakeholder enablement, and ongoing iteration. You’ll work directly with GTM teams to surface high-value business problems and answer them with the right mix of analytics and modeling, translating what you find into decisions that stick. The best person for this role has strong modeling instincts, genuine curiosity about how GTM businesses operate, and the judgment to know when a complex model is the right tool - and when a well-framed SQL query gets you there faster.

This role is based in Raleigh, NC and follows Pendo’s hybrid model: in-office 3 days per week.

What this looks like day-to-day

• Leverage data analysis, machine learning, and predictive modeling to identify opportunities and mitigate risks for our GTM teams, from problem framing through delivery and ongoing iteration
• Work collaboratively with data & AI engineers, analysts, revenue operations, and GTM stakeholders to ensure your work is actionable, interpretable, and clearly connected to business decisions
• Translate model outputs and analytical findings into clear business narratives through slides, write-ups, presentations, and async video
• Leverage AI-assisted development tools (Cursor, Claude Code) to accelerate delivery and prototype faster, while applying the critical thinking to validate, refine, and own the output
• Share and build reusable patterns, model documentation, and technical findings with the broader team
• Answer high-value business questions through analysis and experimentation: develop hypotheses, own the approach, and communicate findings clearly to both technical and non-technical audiences
• Partner with GTM teams to enable adoption of the models and tools you build, making sure they know how to use them and realize the value

You’ve worked alongside revenue teams enough to understand what drives their decisions. You know an insight nobody uses isn’t worth much, so you think about adoption as much as performance. You can take something technical and explain it in a way that makes sense to the people who need to act on it.

You thrive in fast-moving, ambiguous environments. You know when a problem needs a thorough solution and when it just needs a good answer quickly. You’re comfortable making a call with incomplete information and refining it as you learn more.

You’re curious in a way that keeps you sharp.

The tools and techniques in this space change quickly, and you like to stay ahead of that. You don’t usually wait to be told about something new; you’re already trying it out for yourself. You’ve figured out how to make the most of emerging tools, including AI assistants, without handing your judgment over to them.

You make the people around you better. You share what you learn and document what you build to make those around you better. You’re willing to learn from others and make adjustments to make yourself better., * 2-4 years of experience in data science, analytics, or a related quantitative field

• Bachelor’s or master’s education in STEM (science, technology, engineering, math) field
• Experience using statistical computer languages (Python, SQL) to manipulate data and draw insights from large data sets
• Solid grasp of statistical concepts, data analysis, predictive modeling, and machine learning.
• Team oriented and highly agile thinker
• Self-motivated with the ability to work independently and manage multiple priorities concurrently
• Clear communication skills to present complex analyses in a digestible format for diverse audiences
• A true team player with a collaborative, positive approach to solving challenges and supporting colleagues
• Experience with recurring revenue-based business models preferred
• Direct experience working in or alongside a GTM function, such as Sales ops, Marketing analytics, Customer Success, or RevOps
• Comfort navigating ambiguity and moving fast; you can make a good decision with imperfect information and adjust as you learn more, * Experience with LLM-based tooling, prompt engineering, or agentic AI workflows
• Familiarity with BI tools (Omni, Looker, Tableau) for self-serve analytics delivery
• Prior experience working on a small, high-ownership team where scope is broad and expectations are high
• Comfort quantifying the business impact of your work - you can tie model outputs to pipeline, retention, or efficiency metrics, not just model performance
• Background at a B2B SaaS company, ideally with exposure to product analytics or customer health data

Benefits: Highly competitive, employer-heavy coverage (including $0 premium options), strong 401(k) match, equity, and flexible time off.

Compensation: Our salary ranges are based on paying competitively for our size and industry, and are one part of many compensation, benefits and other reward opportunities we provide.

The expected salary range for this role to be performed in North Carolina is USD$133,000 - USD$160,000

EEOC: We are an equal opportunity employer and believe having diverse teams where everyone brings their whole self to Pendo is key to our success. We welcome all people of different backgrounds, experiences, abilities and perspectives.

Accessibility: Pendo is committed to working with, and providing access and reasonable accommodation to, applicants with mental and/or physical disabilities. If you think you may require an accommodation for any part of the recruitment process, please send a request to: accommodation@pendo.io. All requests for accommodations are treated discreetly and confidentially, as practical and permitted by law.

Pendo was founded in 2013 by former product managers, who combined their heads and hearts to build something they wanted but never had as product managers: a simple way to understand and attack what truly drives product success. Our mission is to improve society’s experience with software. Come join one of the fastest-growing startups, supported by best-in-class institutions like Battery Ventures, Salesforce Ventures, Spark Capital and Meritech.