Lead Product Data Scientist
San Francisco, San Francisco County, California, 94102, USA
Listed on 2026-07-10
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IT/Tech
Data Analyst
Lead Data Scientist
As a Lead Data Scientist, you will spearhead the analytical strategy for Docusign's Intelligent Agreement Manager (IAM) and next-generation Agentic AI features. You will serve as the primary bridge between Product and Engineering, setting the vision for telemetry architecture, defining key performance metrics, and orchestrating analytical roadmaps. This role requires moving beyond reactive reporting to proactively shaping the 'test-and-learn' product lifecycle through advanced modeling, experimental design, and cross-functional leadership.
You work directly with stakeholders to turn data into a competitive advantage for our IAM and Agentic initiatives.
This position is an individual contributor role reporting to the Vice President, Operations & Analysis.
Responsibility
- Act as the subject matter expert, translating abstract business goals and abstract product goals into rigorous technical data requirements for Engineering stakeholders
- Partner with Global Data Analytics to oversee the evolution of scalable data pipelines and architectural integrity
- Define and govern the product telemetry strategy, partnering with Engineering to ensure high-fidelity data collection across the integrated IAM suite and Agentic workflows
- Identify patterns in cross-product usage cohorts and adoption signals, synthesizing these into roadmap recommendations for senior leadership and product managers
- Design rigorous experimentation frameworks that move beyond basic A/B testing to optimize complex, cross-product user journeys and LLM-based feature performance
- Oversee the development of automated dashboards and analytical tools that allow business users to independently interpret performance and drive adoption
- Serve as the primary analytical partner to Product, Engineering, and Research, identifying and prioritizing high-impact data opportunities that accelerate IAM and Agentic initiatives
- Communicate complex analytical findings and modeling frameworks to non-technical stakeholders, influencing strategy across functional lines
- Act with a sense of urgency to resolve analytical roadblocks and proactively solicit cross-functional input to ensure data initiatives meet business objectives
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 BringBasic
- BA/BS degree in a quantitative field (e.g., Statistics, Math, CS, Economics) or equivalent practical experience
- 12+ years of experience in product analytics or data science within a SaaS/Cloud environment
- Experience mapping holistic user journeys by joining data across disparate product ecosystems to measure multi-product adoption funnels
- Experience translating abstract product goals into rigorous technical telemetry requirements and partnering with Engineering to implement them
- Experience with SQL for data analysis and validation; experience designing and maintaining automated dashboards in tools like Tableau, Power BI, or HEX
- Experience in statistical analysis, experimental design, and data modeling to solve complex business problems
- Experience communicating complex technical findings and data strategy to non-technical stakeholders
Preferred
- Exceptional ability to lead through influence, navigating cross-functional and organizational lines to align Product and Engineering roadmaps
- Deep expertise in evaluating LLM-based product features and optimizing "human-in-the-loop" agentic workflows
- Experience designing and refining machine learning models with a focus on user intent, behavior prediction, and user segmentation
- Mastery of A/B testing, cohort analysis, and iterative testing methodologies to drive optimization in complex, multi-stage user journeys
- Ability to synthesize…
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