Data Scientist

About the role

Who We Are

At Pave, we're building the industry’s leading compensation platform, combining the world's largest real-time compensation dataset with deep expertise in AI and machine learning. Our platform is perfecting the art and science of pay to give 9,000+ companies unparalleled confidence in every compensation decision.

Top tier companies like OpenAI, McDonald’s, Instacart, Atlassian, Affirm, Ericsson, Synopsys, Stripe, Doordash, Fanatics, Databricks, and Waymo use Pave, transforming every pay decision into a competitive advantage. $190+ billion in total compensation spend is managed in our workflows, and 80% of Forbes AI 50 use Pave to benchmark compensation.

The future of pay is real-time & predictive, and we’re making it happen right now. We’ve raised $175M in funding from leading investors like Andreessen Horowitz (a16z), Index Ventures, Y Combinator, Insight Partners, Atomico, Venture Partners, and Craft Ventures.

The Data Team @ Pave

Data is truly at the heart of what we do here at Pave. So, it’s no surprise that Pave data team members are integral collaborators and strategic owners with company-wide impact, enabling us to build a stellar product experience. The Insights pod is the team that turns Pave’s one-of-a-kind real-time compensation dataset into stories: research reports, market indices, content campaigns, and data products that shape how the market thinks about pay. We're looking for a Data Scientist to join this pod and help us scale our storytelling, serve our customers better, and build the measurement foundation to make smarter decisions about where we invest next.

What You'll Do

- Partner with Marketing to take data stories from brief to published asset: running the analysis, building the narrative, and iterating fast across blogs, reports, social content, and landing pages

- Support Pave's data products, including Pave Data Lab and Market Data, with research, analysis, and special projects that keep our content fresh and differentiated

- Evangelize Pave's compensation community and expertise by fielding data and compensation questions from customers, prospects and internal team members

- Develop a lightweight measurement framework that measures what's working across our content

- Build a deep understanding of Pave's compensation dataset and translate complex findings into clear, compelling narratives for non-technical audiences

What You'll Bring

- 2+ years of experience in a data science, analytics engineering, or advanced analytics role, ideally with exposure to customer-facing or external-facing work

- SQL experience: You're comfortable writing queries (CTEs, window functions, multi-table joins) against large datasets and have a good understanding of complex queries

- Hands on experience in Python for data manipulation / charting to clean, analyze, and visualize data

- Data visualization: You have hands-on experience with a BI or notebook tool such as Tableau, Looker, Power BI, Hex, Mode, or Sigma, and you can turn analysis into clear, compelling charts