Key Focuses
Lead & Develop the Team: Manage and coach a team of decision scientists supporting the Enterprise area. Review and coach on their work, own performance and career development conversations, set clear expectations, and help each person build on their strengths and grow their business and technical skills. Prioritize across multiple concurrent projects, align the team's capacity with the goals of the Enterprise area and the company, and find ways to make the team more efficient, including setting standards for Data and AI tooling.
Player-Coach Technical Leadership: Personally lead strategic analyses in the Enterprise space and be comfortable diving into the details. Set methodological standards for the team, pressure-test causal claims, and coach the team on the right level of rigor for each question. That includes knowing when "good enough to decide" beats "statistically conclusive."
Lead Decision Science for the Enterprise Area: Own the decision science agenda for Enterprise. Partner with stakeholders to define which questions are worth asking, set analytical priorities, and hold the team to a high bar of rigor. The team covers the full Enterprise lifecycle, from campaign-driven traffic through the apply experience, ATS integrations, and candidate-quality signals.
Measure GTM & Sales-Led Initiatives: Evaluate the success of initiatives led by Sales, GTM, and Customer Success. With a smaller base of large customers, randomized tests are often not an option, and sometimes there aren't enough accounts or events for causal inference methods either. You will pick the strongest approach the data can support. That may be a quasi-experimental design, a descriptive before/after read, or a combination of quantitative results with qualitative signals such as customer feedback, Customer Success and Sales input, and account-level context. You will be clear with partners about how confident each conclusion is.
Cross-Functional Partnership & Influence: Serve as the trusted Decision Science partner for Enterprise Product, Engineering, Rev Ops, Sales/GTM leadership, and Customer Success. Influence direction and prioritization within the cross-functional team and find new opportunities to partner. Turn complex quantitative findings into clear, actionable recommendations for technical and non-technical audiences, including senior stakeholders.
Minimum Qualifications
Bachelor's degree in a quantitative field such as mathematics, statistics, computer science, operations research, economics, or equivalent experience.
6+ years of analytics or data science experience in a product/engineering/tech environment.
1+ years of people management experience, including direct responsibility for performance management and career development.
Demonstrated ability to lead data work on important business initiatives while earning the trust of cross-functional and business stakeholders.
Experience measuring impact with both A/B tests and quasi-experimental or causal inference methods (e.g., difference-in-differences, synthetic control, matching) when randomization isn't feasible.
Sound judgment in low-data situations. You can combine limited quantitative evidence with qualitative signals to reach a well-reasoned recommendation, and you communicate the uncertainty honestly.
Strong business acumen and a demonstrated ability to connect data analysis to measurable business outcomes.
Excellent communication and presentation skills, with a track record of synthesizing complex findings for both technical and non-technical audiences.
Preferred Qualifications
Experience with performance marketing campaign measurement and optimization
Experience analyzing customer retention, churn, and expansion in a B2B or enterprise SaaS business.
Experience partnering with Sales, GTM, Rev Ops, or Customer Success teams to evaluate business initiatives.
Experience working with small-sample or account-level data, such as B2B customer bases where each customer has an outsized impact.
Familiarity with recruiting, HR tech, or ATS ecosystems, or with two-sided marketplaces.
As part of our team you’ll enjoy
Competitive salary
Exceptional benefits package
Flexible Vacation & Paid Time Off
Employer-matched 401(k) plan
#LI-Remote
The US base salary range for this full-time position is $177,500-$235,000 Our salary ranges are determined by role, level, and location, and the range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location, role-related knowledge and skills, depth of experience, relevant education or training, and additional role-related considerations.
Depending on the position offered, equity, bonuses, commission, or other forms of compensation may also be provided as part of a total compensation package, in addition to a full range of medical, financial, and other benefits.
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