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Docusign

Runs electronic signing and agreement workflows

GTM Analytics & AI Measurement Director

Data SciencePosted on Nov 11
Full-time

About the Job

Requirements

  • At least 15 years of experience in data science, analytics, or quantitative strategy, including at least 5 years in B2B SaaS go-to-market.
  • At least 12 years of experience and a Master's degree or equivalent experience.
  • Experience with experimental design and causal inference, including A/B testing, difference-in-differences, synthetic control, and uplift modeling.
  • Experience with SQL and Python, including pandas, statsmodels, scikit-learn or similar, and Snowflake or similar cloud data warehouses.
  • Experience with go-to-market metrics, including pipeline, conversion, win rate, sales cycle, net revenue retention, churn, customer acquisition cost payback, and lifetime value.
  • Experience with large language model-based systems and evaluating their output quality, failure modes, and large language model-as-judge methods.
  • Experience translating complex analysis into clear recommendations for executive audiences.

Responsibilities

  • Build core data and analytical products for go-to-market motions in partnership with internal information technology teams.
  • Own measurement strategy for go-to-market artificial intelligence initiatives by defining success, establishing pre-launch baselines, and setting key performance indicator hierarchies spanning adoption, productivity, and revenue outcomes such as pipeline, win rate, cycle time, annual contract value, and retention.
  • Design rigorous evaluations for artificial intelligence deployments, including A/B tests, staged rollouts with holdout groups, and quasi-experimental methods such as difference-in-differences, synthetic control, and propensity matching when randomization is not feasible.
  • Quantify the incremental impact and return on investment of individual artificial intelligence tools and the overall artificial intelligence portfolio, separating artificial intelligence-driven lift from seasonality, territory changes, pricing, and other confounders.
  • Build and maintain a go-to-market leadership impact scorecard tracking adoption, usage depth, productivity gains, and revenue attribution across Sales, Customer Success, Marketing, and Partner teams.
  • Develop forecasting and sizing models to estimate the value of proposed artificial intelligence initiatives before investment and help prioritize the roadmap based on expected business impact.
  • Make data-driven recommendations to scale, iterate on, or sunset artificial intelligence initiatives, and present findings and trade-offs to the Chief Revenue Officer, Chief Financial Officer, and go-to-market leadership.
  • Ensure data instrumentation is incorporated from day one by partnering with artificial intelligence product, Data Engineering, information technology, and Revenue Operations teams.

Desired Qualifications

  • An advanced degree (Master of Science or PhD) in Statistics, Economics, Data Science, Operations Research, or a related quantitative field.
  • Experience measuring the impact of artificial intelligence, automation, or sales productivity tools in a go-to-market organization, ideally from pre-launch baseline through post-rollout return-on-investment readout.
  • Hands-on experience with uplift modeling, heterogeneous treatment effects, or causal machine learning, such as EconML, DoWhy, or CausalML.
  • Experience evaluating large language model-based systems, including output quality scoring, large language model-as-judge frameworks, and linking model quality to business outcomes.
  • Working knowledge of agent frameworks and artificial intelligence workflows, such as LangGraph, CrewAI, AutoGen, or Azure AI Foundry, and prompt design, sufficient to partner with artificial intelligence builders and design appropriate instrumentation.
  • Familiarity with go-to-market data sources such as Salesforce, Gong or other conversation intelligence platforms, Clari, and product usage telemetry.
  • Experience building executive-facing scorecards and dashboards using tools such as Tableau, Looker, or Sigma that tie adoption metrics to revenue outcomes.
  • Background in forecasting or investment sizing models used to prioritize a roadmap or allocate budget.
  • Track record of influencing senior leaders, including Chief Revenue Officers, Chief Financial Officers, and go-to-market vice presidents, to scale, change, or stop programs based on analytical findings.
  • Comfort working in a fast-moving environment that values speed and experimentation while maintaining rigorous statistical standards.

About the Company

Docusign

Runs electronic signing and agreement workflows

Docusign runs electronic signing and agreement management software for businesses, letting people approve contracts online and track the steps around each agreement. Its eSignature product routes documents to signers and records who signed, while contract lifecycle tools organize preparation, negotiation, and approvals. The Intelligent Agreement Management platform stores contracts in a searchable repository and uses AI to extract terms and connect agreement data to business workflows. Customers use its web applications or embed signing through APIs, and pay for subscriptions based on users, features, and document allowances. Docusign was founded in 2003 and is headquartered in San Francisco.

Company size
5,001-10,000
Company stage
IPO
Headquarters
San Francisco, CA
Founded
2003

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