Data Product Manager - Payment Optimization

Company Overview Docusign brings agreements to life. Over 1.5 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 Docusign’s Intelligent Agreement Management 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 As a Technical Product Manager with a strong data and machine learning background in the payments domain, you will drive the analytical and ML strategy for Docusign’s subscription payments. You will frame payment problems as measurable hypotheses, design and interpret experiments with Data Science and Engineering, and translate model outputs into decisioning logic and customer-facing capabilities that improve payment success and retention across multiple processors. You will own the data and ML roadmap for initial and recurring payments, interrogate the data to uncover optimization opportunities, and regularly communicate strategy, experiment results and model performance to senior leadership. This position is an individual contributor role reporting to the Product Management Director.

Responsibility

• Own the data and ML roadmap for initial and recurring payments, identifying where statistical modeling, machine learning and AI automation create measurable business impact, and prioritizing based on expected value, data readiness and technical feasibility
• Translate ML model outputs into shipped product features and concrete decisioning logic, for example turning routing or retry model scores into specific rules that determine how each transaction is processed and validating that those rules perform in production
• Perform exploratory data analysis by writing SQL, building cohort and funnel analyses, and segmenting payment behavior to surface optimization opportunities rather than waiting for analysis to be handed to you
• Design and own the experimentation program: define hypotheses, choose metrics, determine sample sizes and statistical power, guard against pitfalls such as peeking, multiple comparisons and novelty effects, and interpret results rigorously
• Partner with Data Science to scope, evaluate and ship models such as payment routing, retry optimization and churn prediction, and define evaluation criteria (for example precision and recall, calibration and business-metric lift) before they ship
• Establish the data foundation by defining instrumentation, data quality standards, feature definitions and monitoring required to train, evaluate and detect drift in production models
• Translate model behavior and statistical findings into clear requirements and use cases for Engineering, Data Science and UX, driving initiatives from concept to launch
• Monitor and act on KPIs such as payment success and authorization rates, passive churn, conversion, model precision and recall, and reconciliation accuracy
• Build dashboards and self-serve analytics that make payment performance legible to leadership and partner teams
• Partner with Legal, Risk, Finance, Engineering and Compliance to ensure responsible, explainable and auditable use of AI in payment decisioning 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

• Bachelors degree in Engineering, Computer Science, Statistics, Applied Math or a similar quantitative discipline
• 5+ years overall professional experience including approximately 3 years in digital product management
• Experience in data science, analytics or ML engineering in addition to product management experience
• Hands-on data analysis experience including fluency in SQL and comfort using Python or R to independently run analyses
• Experience translating ML model outputs into shipped product capabilities or decisioning and routing rules and validating their impact in production
• Experience working directly with UX, Engineering and Data Science or Testing teams on payment-related or other data-intensive initiatives
• Knowledge of domestic and international payment options including cards, direct debits, alternate payment methods and gateways in a recurring or subscription environment
• Experience with payment offerings in a global context and associated optimizations that reduce friction, drive conversion and improve retention

Preferred

• Advanced degree (MS or MBA) in Engineering, Computer Science, Statistics, Applied Math or a related quantitative field
• Hands-on experience with experimentation platforms (for example A/B testing frameworks), analytics or BI tools and modern data stacks
• Direct experience with ML applications in payments such as authorization-rate optimization, intelligent routing, churn prediction or anomaly detection in reconciliation
• Familiarity with causal inference methods (for example diff-in-diff, instrumental variables, uplift modeling) for situations where clean A/B tests are not possible
• Familiarity with regulations and compliance standards (for example GDPR and PSD2) and their impact on payments, subscriptions and automated decisioning
• Experience driving complex projects across a large, cross-functional organization
• Written and verbal communication skills including the ability to translate technical findings for executives and lead through influence across teams Life at Docusign

Working here Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what’s right, every day. At Docusign, everything is equal. We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you’ll be loved by us, our customers, and the world in which we live.

Accommodation Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at accommodations@docusign.com. If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at taops@docusign.com for assistance. Applicant and Candidate Privacy Notice