Technical Product Manager - Payment Optimization

DocuSign DocuSign · Enterprise · Bangalore, India · Marketing & Communications

Technical Product Manager with a strong data and machine learning background in the payments domain to drive the analytical and ML strategy for Docusign’s subscription payments. The role involves framing payment problems, designing and interpreting experiments, translating model outputs into decisioning logic and customer-facing capabilities to improve payment success and retention. Responsibilities include owning the data and ML roadmap, performing exploratory data analysis, designing and owning the experimentation program, partnering with Data Science to ship models (e.g., payment routing, retry optimization, churn prediction), establishing the data foundation, translating model behavior into requirements, monitoring KPIs, building dashboards, and partnering with Legal, Risk, Finance, Engineering, and Compliance for responsible AI use.

What you'd actually do

  1. 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
  2. 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
  3. 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
  4. 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
  5. 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

Skills

Required

  • SQL
  • Python or R
  • Product Management
  • Data Science
  • Analytics
  • ML Engineering
  • Payments domain experience
  • Experimentation design
  • Translating ML model outputs into shipped product capabilities or decisioning and routing rules
  • Working directly with UX, Engineering and Data Science or Testing teams

Nice to have

  • Advanced degree (MS or MBA)
  • Experimentation platforms (A/B testing frameworks)
  • Analytics or BI tools
  • Modern data stacks
  • ML applications in payments (authorization-rate optimization, intelligent routing, churn prediction, anomaly detection)
  • Causal inference methods
  • Regulations and compliance standards (GDPR, PSD2)

What the JD emphasized

  • strong data and machine learning background
  • translate model outputs into shipped product features
  • own the data and ML roadmap
  • Partner with Data Science to scope, evaluate and ship models
  • define evaluation criteria
  • responsible, explainable and auditable use of AI

Other signals

  • drive the analytical and ML strategy
  • translate model outputs into decisioning logic and customer-facing capabilities
  • own the data and ML roadmap
  • Partner with Data Science to scope, evaluate and ship models
  • Translate ML model outputs into shipped product features