GTM Analytics & AI Measurement Director

Company Overview Docusign brings agreements to life. More than 1.8 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using the Docusign AI-native IAM platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM). What you'll do AI is at the center of Docusign's strategy, from the AI powering our Intelligent Agreement Management platform to the tools transforming how our go-to-market teams sell, renew, and serve customers. As we scale AI across our GTM organization, we're investing in the analytical rigor to know what's working, measure its impact, and direct investment where it creates the most value. This role sits at the heart of that effort. Docusign is seeking a GTM Analytics & AI Measurement Director to serve as the analytical authority on whether, where, and how much AI is moving the needle for our go-to-market organization. As Docusign deploys AI across Sales, Customer Success, Marketing, and Partner teams, this role will answer the questions leadership cares about most: Is it working? How much value is it creating? Where should we invest next? You'll build the measurement framework for every GTM AI initiative, from setting baselines and designing experiments before launch to quantifying incremental impact on pipeline, win rates, sales cycle, retention, and productivity after rollout. You'll bring rigor to a hard problem: separating AI-driven lift from the many other forces that shape GTM performance. You'll do it with controlled experiments, holdout designs, and causal inference methods. You'll partner closely with AI Product, RevOps, Data Engineering, and IT teams so that new AI tools are instrumented from day one. You'll also work with GTM leaders to turn findings into decisions: scale what works, fix what's underperforming, and retire what isn't delivering. Beyond AI, you'll act as the lead for developing key analytic products to inform GTM decisions, applying the same experimental and causal rigor. Your work will directly shape how Docusign invests in AI and how leadership understands its return. This position is an individual contributor role reporting to the VP of Growth Strategy & Operations. Responsibility Build core data and analytical products to serve GTM motions in partnership with internal IT teams Own the measurement strategy for GTM AI initiatives: define what success looks like, establish pre-launch baselines, and set the KPI hierarchy from adoption to productivity to revenue outcomes (pipeline, win rate, cycle time, ACV, retention) Design rigorous evaluations for AI deployments, including A/B tests, staged rollouts with holdout groups, and quasi-experimental methods (difference-in-differences, synthetic control, propensity matching) where randomization isn't feasible Quantify the incremental impact and ROI of individual AI tools and of the overall AI portfolio, separating AI-driven lift from seasonality, territory changes, pricing, and other confounders Build and maintain an impact scorecard for GTM leadership that tracks adoption, usage depth, productivity gains, and revenue attribution across Sales, CS, Marketing, and Partner teams Develop forecasting and sizing models to estimate the value of proposed AI initiatives before investment, and help prioritize the roadmap based on expected business impact Make data-driven recommendations to scale, iterate on, or sunset AI initiatives, and present findings and trade-offs to the CRO, CFO, and GTM leadership Ensure data instrumentation is incorporated from day one by partnering with AI product, Data Engineering, IT, and RevOps teams Job Designation Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation) Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law. What you bring Basic 15+ years of experience in data science, analytics, or quantitative strategy, with 5+ years in B2B SaaS GTM 12+ years of experience and a Master's degree and equivalent experience Experience with experimental design and causal inference (A/B testing, diff-in-diff, synthetic control, uplift modeling) Experience with SQL and Python (pandas, statsmodels, scikit-learn or similar); experience with Snowflake or similar cloud data warehouses Experience with GTM metrics: pipeline, conversion, win rate, sales cycle, NRR, churn, CAC payback, LTV Experience with LLM-based systems and how to evaluate them (output quality, failure modes, LLM-as-judge) Experience turning complex analysis into clear recommendations for executive audiences Preferred Advanced degree (MS or PhD) in Statistics, Economics, Data Science, Operations Research, or a related quantitative field Experience measuring the impact of AI, automation, or sales productivity tools in a GTM organization, ideally from pre-launch baseline through post-rollout ROI readout Hands-on experience with uplift modeling, heterogeneous treatment effects, or causal ML (e.g., EconML, DoWhy, CausalML) Experience evaluating LLM-based systems, including output quality scoring, LLM-as-judge frameworks, and linking model quality to business outcomes Working knowledge of agent frameworks and AI workflows (e.g., LangGraph, CrewAI, AutoGen, Azure AI Fo