Head of Data Science

Paddle
United Kingdom, Portugal, Ireland
Workplace: RemoteFull timeFunction: Data Science & Machine LearningSkills: ["Measurement","Experimentation","Experimentation design","Governance"]

Build Paddle’s data science capability from scratch, turning merchant-of-record payment and subscription data into production automated decisioning. Own the end-to-end pipeline from analysis and feature engineering to training/evaluation of traditional ML and agentic systems, then run monitoring, retraining, drift response, and A/B tests. Partner with Product, Payments, Engineering, Risk, and Finance, and later hire a hub-and-spoke team to scale the production stack and governance.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
Paddle
Paddle
19 hours ago

Head of Data Science

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 5 hours agoStatus: Live

Job Summary

Build Paddle’s data science capability from scratch, turning merchant-of-record payment and subscription data into production automated decisioning. Own the end-to-end pipeline from analysis and feature engineering to training/evaluation of traditional ML and agentic systems, then run monitoring, retraining, drift response, and A/B tests. Partner with Product, Payments, Engineering, Risk, and Finance, and later hire a hub-and-spoke team to scale the production stack and governance.
Location: United Kingdom, Portugal, Ireland
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Sr. Director level

Key Responsibilities

  • •Prioritise the highest-impact data science opportunities, build a value-based use-case backlog, size candidates, and sequence work with Product, Risk, RevOps, and Finance.
  • •Personally deliver the first automated decisioning system end to end, including analysis/back-testing, feature engineering, model/policy/agent development, deployment, and shadow/A-B tests.
  • •Operate what’s deployed by owning monitoring, retraining, drift response, incident handling, and rollback alongside engineering teams that call the decisioning service.
  • •Work across traditional ML and agentic systems, selecting the right approach (propensity/uplift, rule-based policy, or agents with tools) and applying appropriate evaluation methods.
  • •Establish the production stack and governance for automated decisioning, set boundaries with analytics/data teams, and later hire and lead a hub-and-spoke team embedded in business areas.

Pay and Benefits

Perks:Paid LeaveLearning Budget

Key Requirements

  • •Experience leading data science or ML teams that own production systems and moved a commercial metric while continuing to run reliably afterwards.
  • •Hands-on ability to write SQL and Python, engineer features, evaluate models/agents, and deliver the first system end to end.
  • •Deep understanding of both traditional ML and agentic systems, including propensity/uplift modeling and how agent workflows differ in practice.
  • •Proven experience operating live ML/agent systems: monitoring, retraining, incident response, and rollback/on-call realities.
  • •Ability to hire, level, and develop senior data scientists and machine learning engineers, and set standards for a new function.
Experience:FintechPaymentsSubscriptionsHigh-volume operations
Skills:MeasurementExperimentationExperimentation designGovernance
Tech Stack:SQLPythonMachine learningAgentic systemsA/B testingFeature pipelinesModel registryInference servicesFeature storesDrift detectionTrace observabilityMonitoringRetraining

Company Brief

Paddle
Paddle is a merchant-of-record platform that handles payments, billing, taxes, fraud and compliance for SaaS and digital product companies, enabling sellers to manage global commerce and subscriptions through a single payments infrastructure.
Industry: Fintech Infrastructure
Company Size: Large (251 to 1,000 employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series D
Headquarters: London, United Kingdom
Founded: 2012
Glassdoor
Glassdoor: 3.3
WebsiteLinkedInGlassdoor