Growth Data Scientist

Docusign•San Francisco, CA

11d•Hybrid

About The Position

We’re looking for a strategic, execution-minded Growth Data Scientist to be the data science engine behind Docusign’s self-serve retention motion — ensuring our customers stay active, get value, and renew through intuitive, data-driven product and lifecycle experiences. Partnering closely with a cross-functional squad — including Growth, Product, Lifecycle Marketing, Customer Success, Engineering, and Strategy & Ops — you will use data and insights to help build and scale the systems that prevent churn and drive durable customer value. You will lead strategic analyses and hands-on experimentation to uncover, validate, and scale new ways to reduce active and partial churn by improving usage, value realization, plan fit, and save-flows. You will sit at the center of Docusign’s retention strategy, translating behavioral signals, product telemetry, and customer intent into decisions that shape how customers stay, downgrade, upgrade, or renew. In this high-impact, hands-on role, you will own retention performance readouts, design and analyze cancel-save and customer lifecycle experiments, and deliver clear, compelling insights that directly inform product, marketing, and go-to-market execution. You will help Docusign evolve to a proactive, intelligent, and customer-centric retention engine — where the right intervention happens at the right moment in the customer journey. Our ideal candidate combines best-in-class analytical skills, a strong strategic mindset with a bias for execution, a passion for experimentation and continuous learning, and a proven record of turning usage, churn signals, and customer behavior into measurable retention and revenue impact. This position is an individual contributor role reporting to the Director, Growth Analytics.

Requirements

2+ years of experience in Analytics, Data Science, or related roles - ideally spanning product/growth analytics, strategic/consulting analytics, or sales‑operations analytics in a SaaS environment
Experience with experimentation frameworks (A/B testing, causal inference) and strategic analysis
Experience with SQL plus Python or R, and strong command of visualization tools such as Tableau, Looker, or equivalent
Demonstrated ability to distill complex analytical findings into concise, actionable recommendations for executive audiences

Nice To Haves

Excellent communication and presentation skills with the ability to present complex data analysis, insights, and recommendations to senior leadership
Prior partnership with Growth Product Management or Marketing, influencing strategy through data‑driven insights.
Experience operating in hybrid self‑serve / sales‑assisted SaaS business models
MBA, MS, or PhD in a quantitative discipline (e.g., Statistics, Computer Science, Economics)

Responsibilities

Translate complex data and analyses into clear, data‑backed recommendations for senior leadership, influencing strategic direction across Growth, Product, Marketing, Sales, and Customer Success
Provide regular reporting on key metrics to executive leadership, highlighting successes, identifying risks, and recommending proactive solutions
Design, implement, and analyze experiments (A/B tests, causal inference) that inform product and GTM decisions and quantify business impact
Identify growth opportunities and risks, using forecasting and scenario modeling to guide resource allocation and prioritization
Apply advanced analytical techniques (e.g., predictive modeling, customer segmentation, LTV analysis) to understand customer behavior, forecast outcomes, and inform strategic initiatives

Benefits

Bonus: Sales personnel are eligible for variable incentive pay dependent on their achievement of pre-established sales goals. Non-Sales roles are eligible for a company bonus plan, which is calculated as a percentage of eligible wages and dependent on company performance.
Stock: This role is eligible to receive Restricted Stock Units (RSUs).
Paid Time Off: earned time off, as well as paid company holidays based on region
Paid Parental Leave: take up to six months off with your child after birth, adoption or foster care placement
Full Health Benefits Plans: options for 100% employer paid and minimum employee contribution health plans from day one of employment
Retirement Plans: select retirement and pension programs with potential for employer contributions
Learning and Development: options for coaching, online courses and education reimbursements
Compassionate Care Leave: paid time off following the loss of a loved one and other life-changing events

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