Job description

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 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 haves Experience with compensation and labor market data Experience with data tools like dbt, Hex, Claude code Experience building customer-facing data products Compensation, It's What We Do. At Pave, we believe compensation should be as thoughtful as the people we hire. Your total rewards package includes meaningful equity, best-in-class medical, dental, and vision coverage, unlimited PTO, and region-specific benefits designed around your life — not just your role. Your level and compensation are determined by your experience and how you show up throughout the interview process. We're always happy to walk you through how we think about leveling — just ask. Targeted cash compensation for this role: P2: $115,000 - $144,000 P3: $139,000 - $174,000 Benefits @ Pave At Pave, growth isn't a perk — it's the point. As you develop, your role expands, your responsibilities deepen, and your compensation reflects the impact you're making. What we offer Your Health, Fully Covered: Comprehensive medical, dental, and vision coverage for you and your family, with a range of options designed to meet you where you are. Time That's Actually Yours: Flexible PTO and the freedom to work from anywhere in the world for up to a month — because life doesn't pause, and neither should you. Fuel for the Work: Lunch and dinner stipends plus fully stocked kitchens, so you can stay energized without thinking twice about it. Room to Keep Growing: A quarterly education stipend to invest in the skills and knowledge that matter most to you. Support When It Matters Most: Robust parental leave so you can be fully present for the moments that count. Getting Here, Made Easier: A commuter stipend to support the in-person collaboration that makes great work happen. Life @ Pave Founded in 2019 with a clear purpose and a team that has never wavered from it, Pave has grown into a global force in compensation management — giving thousands of companies the tools to take control, build confidence, and earn credibility in every pay decision they make. And we're just getting started. Headquartered in San Francisco's Financial District, with regional hubs in New York City's Flatiron District, Salt Lake City, Kraków (Poland), and the United Kingdom — wherever you're based, you'll find the same thing: people who genuinely care about the work, each other, and the customers that rely on Pave. We run a hybrid culture that brings teams together in person 4 days a week — and every Friday, the whole company gathers for our Team Sync: breakfast, new hire welcomes, product updates, fireside chats, and yes, the occasional Kahoot. It's one of the things people notice when they join us — that we truly enjoy spending time together. Our culture is shaped by five values we live every day: Be Intellectually Honest — Truth over comfort. We face reality clearly and speak directly, even when it's hard. Play to Win — We're not here to participate. We're here to be the #1 compensation platform in the world, and we act like it. Uphold the Pave Platinum Standard — We hold ourselves to the highest bar — for our customers, our data, and each other. One Team — We win and lose together. Titles don't drive decisions here — shared goals do. Hug of Jawn — Hard to define, impossible to miss. Ask your recruiter. Our Vision: Unlock a labor market built on trust. Our Mission: Build confidence in every compensation decision. We build software that transforms how companies pay their people — and we believe the team behind that software deserves the same thoughtfulness. If you're ready to help shape the future of compensation alongside people who are smart, humble, and genuinely motivated by the problem we're solving, we'd love to meet you. Still deliberating? Just apply! We're always excited to meet people who are eager to contribute. Pave uses automated tools, including AI-based fraud detection, to verify applicant identity and protect the integrity of our hiring process.

Requirements

Must-haves

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
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
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-haves

Experience with compensation and labor market data
Experience with data tools like dbt, Hex, Claude code
Experience building customer-facing data products
Compensation, It's What We Do.
Targeted cash compensation for this role: P2: $115,000 - $144,000 P3: $139,000 - $174,000
Benefits @ Pave
At Pave, growth isn't a perk — it's the point. As you develop, your role expands, your responsibilities deepen, and your compensation reflects the impact you're making.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningsqlpython

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Benefits

Benefits detected in the listing.

Dental

Vision

Pto

Parental Leave