Senior Domain Expert

Do you want to empower organizations to build smarter compensation strategies while ensuring fair pay for all employees? Syndio is the leading pay governance and compensation intelligence platform. We help organizations make better pay decisions at every stage of the compensation lifecycle, from leveling and offers to promotions and merit. Our platform gives HR, compensation, and finance leaders the data and decision support they need to govern pay fairly, compliantly, and with confidence. We partner with many of the world’s most recognized and respected enterprises, helping them implement leading-edge compensation solutions with expert guidance and analyzing pay for over 10 million employees across the world. Join us in our mission to help companies make smarter pay decisions they can trust! About the role Syndio is the leader in compensation equity and pay decision intelligence, helping the world’s largest employers make fair, defensible, and transparent pay decisions at scale. As Decisions moves to general availability and our enterprise footprint grows, the quantitative depth behind our recommendations has to keep pace. The Senior Domain Expert (Labor Economics, Statistics, or IO) is a hands-on quantitative practitioner on the Applied Pay Intelligence team. You work directly with our customers and are a senior individual contributor role that leads a small squad. You are the person our customers, our product, and the rest of the team turn to when the methodology has to hold up under scrutiny. You own an area of Syndio’s methodology and asset library, build the 1:many resources that scale your expertise across the customer base, partner directly with Product to embed methodology into Decisions and Essentials, and show up in the customer conversations where the numbers and the reasoning have to be right. You will translate custom analytics into product requirements and support product and development teams as needed on design and implementation plans, partner with the data science and development teams to ensure the product helps advance the outcomes of our total rewards customers. Why this job is exciting Lead a squad. You will be an individual contributor but you will own an area of Syndio’s methodology and content — comparator group logic, regression modeling, remediation methodology, or a related domain. Guide the squad’s roadmap, prioritize what gets built, and hold the technical bar for the work that ships. Apply methodology in complex customer situations. Work through the statistical questions customers can’t resolve inside the product: unusual workforce structures, small-group modeling, contested comparator choices, novel regulatory tests. Bring the methods, explain the tradeoffs, defend the approach. Build 1:many resources. Turn recurring methodological questions into durable content — customer briefings, methodology guides, model documentation, worked examples — so recurring questions do not require a recurring meeting. Partner with Product. Work directly with Product and AI teams to embed methodology into Decisions and Essentials. Translate quantitative rigor into product logic, review model outputs, catch the edge cases before customers do. Show up for the moments that matter. Anchor customer QBRs, regulatory inflection points, and board-adjacent conversations where the methodology has to hold. Not every meeting — the ones where getting the math and the framing right changes the outcome. Feed the frameworks upward. Surface what current frameworks don’t yet cover. Bring specific customer patterns and methodological gaps to the Principal-level colleagues and to Product so the platform’s intelligence keeps compounding. About you 5+ years of hands-on quantitative work in labor economics, statistics, econometrics, industrial-organizational psychology, or a directly related field, applied to compensation, workforce, or pay equity questions. Deep facility with regression modeling and comparator methodology. You can build a defensible pay equity model, explain what it does and does not tell you, and defend the choices behind it in front of a non-technical audience. Demonstrated ability to translate quantitative rigor into language a CHRO, a works council, or a CSM can act on, without losing the substance. Experience embedding methodology into a product, a tool, or a repeatable workflow that other people execute — not just running the analysis yourself. Strong judgment on the difference between what the data supports and what the customer wants it to say, and comfort holding that line. Track record of building content, documentation, or enablement materials that reduce reliance on your calendar over time. Comfort thinking about how quantitative expertise translates into AI-mediated product capability. Experience in HR tech, compensation, people analytics, or a similarly data-intensive enterprise domain is a strong plus. Why you’ll love it here: 💰 Competitive Compensation. For this role our salary is targeted at $143,000 -$160,000 per year. Final offer amounts are determined by factors such as experience and expertise. We take a geo neutral approach to compensation within the US, meaning that we pay based on job function and level, not location. 🏆 Syndio Equity. So you can share in Syndio’s success. 🏝 Flexible Vacation Policy. We encourage our team to recharge when they need to, plus paid sick & safe time, compassion leave, and voting leave. Paid parental leave 🩺 Medical, Dental, Vision. Syndio pays 90% of employee premiums, and 50% for dependents. 🏥 Life Insurance & Disability. Syndio covers the full premium. 🏦 401(k). To help you save for your future Fully remote model - #LI-Remote The interview overview Below you’ll find an outline of the interview plan for our Senior Domain Expert position. Please note that this is what we expect the process to look like; we may ask you for supplemental information or require an additional step before making a final decision. 30 min interview with a member of our Talent Team 45 minute zoom interview with the Hiring Manager (VP Applied Pay Intelligence) 45 minute zoom interview with a Product partner Panel interview with Applied Pay Intelligence team members