• Design, build, and continuously refine a scalable taxonomy of jobs, sub-domains, distinct user tasks, tools, and data used across various job roles. • Plan and execute both qualitative and quantitative user research to inform and validate the taxonomy. • Leverage AI-moderated user research tools to conduct, synthesize, and extract qualitative insights from large user cohorts efficiently. • Apply basic statistical methods to evaluate, rank, and prioritize tasks based on user importance, frequency, and current pain points. • Partner with Product, Design, AI Research, Operations and Engineering to ensure the taxonomy informs product strategy and feature development. • Translate complex, multi-layered research data into clear, actionable frameworks, user models, and documentation.

Role Description We're hiring a Staff Decision Scientist to be strategic partners embedded with product, engineering, marketing, and finance teams. People who shape what gets built, how we grow, and where we invest. You'll own the analytical narrative for your area and deliver insights that directly change roadmaps and resource allocation. The output is decisions, not dashboards. You'll also help make the AI-native organization a reality, shaping the tools and workflows that let automation take on more so the team can go deeper. This is not a production ML role (we have a dedicated Data Science / MLE team for that). Your primary tools are statistical inference, clear thinking, and the judgment to know which question matters most. You'll report into the Data & Analytics leadership team and work alongside data engineers, data scientists, and ML engineers. For candidates based in the US, the salary range for this position is $148,000 to $218,500 USD. For candidates based out of Canada, the salary range for this position is 164,000 to $193,500 CAD. We take into consideration an individual's background and experience in determining final salary; therefore, base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience. The compensation package includes a wide range of medical, dental, vision, financial, and other benefits, as well as equity. Qualifications - 8+ years in an analytics, data science, or decision science role at a consumer tech company - Advanced degree in a quantitative field (economics, statistics, quantitative social science, operations research) or equivalent practical experience - Demonstrated experience with causal inference methods in applied settings (e.g., difference-in-differences, instrumental variables, regression discontinuity, synthetic controls, propensity score matching) - Track record of influencing product or business strategy through data, with specific examples of cross-functional impact - Experience with experimentation platforms (Statsig, Optimizely, or similar) - Proficiency in SQL and Python/R for statistical analysis Requirements - Problem-solving mindset: You structure ambiguous problems precisely before reaching for a tool, AI or otherwise. - Ownership mentality: You take responsibility from framing the question through delivering the recommendation and tracking its impact. You're accountable for decisions changed, not analyses delivered. - AI-native working style: You use AI tooling (Claude Code or equivalent) as a genuine development partner: delegating discrete tasks, reviewing outputs critically, and running parallel workstreams. - Curiosity and initiative: You don't wait for the roadmap to tell you what to analyze. You dig into data because you're genuinely curious about how things work. - Influence at scale: You've shaped strategy at the business unit level by framing the right question and making the evidence impossible to ignore. Benefits - Competitive pay and benefits. - Medical, dental, vision, life and disability insurance plans (100% paid for US employees). We offer supplemental plans for medical and dental for Canadian employees. - 401(k) plan with company matching program in the US and RRSP with DPSP plan for Canadian employees. - Employee Assistance Program (EAP) for mental wellness. - Flexible PTO and 12 company-wide days off throughout the year. - Winter and Summer Weeklong Synchronized Company Shutdowns. - Learning & Development programs. - Equipment, tools, and reimbursement support for a productive remote environment. - Free Life360 Platinum Membership for your preferred circle. - Free Tile Products.

Role Description We're hiring a Lead Decision Scientist to be strategic partners embedded with product, engineering, marketing, and finance teams. People who shape what gets built, how we grow, and where we invest. You'll own the analytical narrative for your area and deliver insights that directly change roadmaps and resource allocation. The output is decisions, not dashboards. You'll also help make the AI-native organization a reality, shaping the tools and workflows that let automation take on more so the team can go deeper. This is not a production ML role (we have a dedicated Data Science / MLE team for that). Your primary tools are statistical inference, clear thinking, and the judgment to know which question matters most. You'll report into the Data & Analytics leadership team and work alongside data engineers, data scientists, and ML engineers. For candidates based in the US, the salary range for this position is $133,000 to $195,000 USD. For candidates based out of Canada, the salary range for this position is 147,500 to 173,000 CAD. We take into consideration an individual's background and experience in determining final salary - therefore, base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience. The compensation package includes a wide range of medical, dental, vision, financial, and other benefits, as well as equity. Qualifications - 6+ years in an analytics, data science, or decision science role at a consumer tech company - Advanced degree in a quantitative field (economics, statistics, quantitative social science, operations research) or equivalent practical experience - Demonstrated experience with causal inference methods in applied settings (e.g., difference-in-differences, instrumental variables, regression discontinuity, synthetic controls, propensity score matching) - Track record of influencing product or business strategy through data, with specific examples of cross-functional impact - Experience with experimentation platforms (Statsig, Optimizely, or similar) - Proficiency in SQL and Python/R for statistical analysis Requirements - Problem-solving mindset: You structure ambiguous problems precisely before reaching for a tool, AI or otherwise. - Ownership mentality: You take responsibility for your work from framing the question through delivering the recommendation and tracking its impact. - AI-native working style: You use AI tooling (Claude Code or equivalent) as a genuine development partner: delegating discrete tasks, reviewing outputs critically, and running parallel workstreams. - Curiosity and initiative: You don't wait for the roadmap to tell you what to analyze. You dig into data because you're genuinely curious about how things work. Benefits - Competitive pay and benefits. - Medical, dental, vision, life and disability insurance plans (100% paid for US employees). We offer supplemental plans for medical and dental for Canadian employees. - 401(k) plan with company matching program in the US and RRSP with DPSP plan for Canadian employees. - Employee Assistance Program (EAP) for mental wellness. - Flexible PTO and 12 company wide days off throughout the year. - Winter and Summer Weeklong Synchronized Company Shutdowns. - Learning & Development programs. - Equipment, tools, and reimbursement support for a productive remote environment. - Free Life360 Platinum Membership for your preferred circle. - Free Tile Products.

• Lead the Continued Development of the Jobs Engine: Own the architecture, integrity, and continuous expansion of Wonderlic’s AI job analysis system, which ingests labor market data from O*NET, LinkedIn, Indeed, and other sources to extrapolate cognitive complexity ratings, norm groups, and occupational interest profiles for thousands of jobs. • Act as an Expert on AI Implementation Across the Organization: Partner with product managers, engineers, and I-O psychologists to translate scientific requirements into AI-powered systems and ensure those systems meet the standards the work demands. • Drive Scientific Rigor: Apply I-O psychology principles - adverse impact consideration, norm group construction, and evidence-based evaluation standards - to every system you build.