Data Scientist

<div class="content-intro"><h3><span style="font-weight: 400; color: #4065ff;"><strong>Who We Are</strong></span></h3> <p><span style="font-size: 12pt;">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.</span></p> <p><span style="font-size: 12pt;">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 <a href="https://www.forbes.com/lists/ai50/">Forbes AI 50</a> use Pave to benchmark compensation.</span></p> <p><span style="font-size: 12pt;">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.</span></p></div><h3><span style="font-size: 14pt;"><strong><span style="color: #4065ff;">The Data Team @ Pave</span></strong></span></h3> <p><span style="font-size: 12pt;">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.</span></p> <h3><span style="color: rgb(64, 101, 255); font-size: 14pt;"><strong>What You'll Do</strong></span></h3> <ul> <li style="font-size: 12pt;"><span style="font-size: 12pt;">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</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">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</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Evangelize Pave's compensation community and expertise by fielding data and compensation questions from customers, prospects and internal team members</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Develop a lightweight measurement framework that measures what's working across our content</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Build a deep understanding of Pave's compensation dataset and translate complex findings into clear, compelling narratives for non-technical audiences</span></li> </ul> <h3><span style="color: rgb(64, 101, 255); font-size: 14pt;"><strong>What You'll Bring</strong></span></h3> <ul> <li style="font-size: 12pt;"><span style="font-size: 12pt;">2+ years of experience in a data science, analytics engineering, or advanced analytics role, ideally with exposure to customer-facing or external-facing work</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">SQL experience: You're comfortable writing queries (CTEs, window functions, multi-table joins) against large datasets and have a good understanding of complex queries</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Hands on experience in Python for data manipulation / charting to clean, analyze, and visualize data</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">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</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">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</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">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</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">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</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, Economics, Mathematics, or another relevant field</span></li> </ul> <h3><span style="color: r