Data Scientist

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 , 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 DoPartner 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 Bring2+ years of experience in a data science, analytics engineering, or advanced analytics role, ideally with exposure to customer-facing or external-facing workSQL 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

Communication and data storytelling:
You can turn a messy, open-ended question into a clear narrative for both technical and non-technical audiences, and your analyses have led to new initiatives, product features, or metric movement

Marketing mindset:
You're excited to use data for storytelling and growth, including trend reports, blog content, and external presentations, and you're willing to be a public-facing voice for our data

Self-direction and focus on impact:
You thrive with ambiguity, take a loosely defined problem from question to answer, and prioritize work that measurably improves our product and business

Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, Economics, Mathematics, or another relevant field

Nice to…