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Data Scientist

🏢 Paveakatroveinformationtechnologies · 📍 San Francisco, California, United States 💰 $115,000 - $144,000 / yr
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Position Summary & Responsibilities

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
🎯 Candidate Preparation Guide For Paveakatroveinformationtechnologies Applicants

Key Role Competencies & Evaluation Highlights

Key Role Focus:

Measuring compensation data intelligence, enterprise SaaS compensation workflows, and secure data handling standards.

📋 Preparation Priorities (Key Areas to Clarify):
  • 1. Treating compensation data carelessly without strict confidentiality protocols
  • 2. Failing to understand pay equity, compliance, and labor market dynamics
  • 3. Building rigid systems that cannot adapt to complex merit matrix configurations
✨ Recommended Role Alignment Hook:

I engineer intelligent compensation infrastructure that turns messy labor market data into clear, equitable, and strategic pay strategies.

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