Head of Data Science

• Join Paddle, the Merchant of Record that removes payment fragmentation for digital product companies, in a full-time remote role. • Build Paddle’s data science capability from the ground up as its founding hire. • Own automated decisioning inside the product, across both traditional machine learning and agentic systems. • Use a rare data position combining subscription and pricing context with granular payment outcomes. • Spend the first quarters building hands-on rather than managing, then hire and lead an embedded team. • Report to the VP of Data and partner with Product, Payments, Engineering, Risk and Finance.

• Bring experience leading data science or ML teams that own systems in production. • Show deployments that moved a commercial metric and kept running afterwards. • Stay hands-on now, writing SQL and Python, engineering features and evaluating models. • Bring experience across both traditional ML and agentic systems, and be clear on how they differ. • Show experience running live systems, including monitoring, retraining, incident response and rollback. • Stay pragmatic about method, arguing for rules or heuristics where they capture most of the value. • Work comfortably from an undefined starting point and defend your own view to executives. • Bring strength in experimentation, uplift modelling and back-testing. • Hold your own work to a financial number that Finance will scrutinise. • Speak fluently about training pipelines, model registries, inference services and drift detection. • Hire, level and develop senior data scientists and ML engineers. • Be based in the UK, Ireland or Portugal.

• Bring experience in payments, fintech, subscriptions or another regulated transactional domain. • Show experience treating regulated ML as a design constraint, including model risk assessment and DPIAs. • Bring familiarity with GDPR, the EU AI Act and payments obligations. • Show experience building a data science function from scratch.

• Build a value-based use-case backlog across payment performance, revenue recovery, growth intelligence and risk. • Size the leading candidates and decide sequencing with Product, Risk, RevOps and Finance. • Personally deliver the first system end to end, from analysis and features through deployment and A/B testing. • Operate what you deploy, owning monitoring, retraining, drift response, incidents and rollback. • Choose honestly between propensity models, rule-based policies and agents with evals and trace observability. • Hire senior data scientists and ML engineers, and set the standards the function runs on. • Establish the production stack alongside Data Platform and Engineering. • Own value capture, translating metric movement into financial numbers co-signed by Finance. • Set the governance model for automated decisioning with Legal, Privacy, Compliance and Risk. • Define boundaries with Product Science, Analytics Engineering, Data Platform and AI Enablement.

• Work remotely as part of a digital-first company, or from one of Paddle’s hubs. • Take unlimited holidays. • Get 4 months of paid family leave regardless of gender. • Use an annual learning fund plus regular internal and external training. • Build a brand-new function with a clear mandate and executive backing. • Join a transparent, collaborative and respectful culture.

Paddle offers digital product companies a different approach to payment infrastructure, acting as a Merchant of Record so they avoid assembling and maintaining a complex stack of payments apps and services. Its model gives it subscription and pricing context alongside granular payment-outcome data across thousands of software businesses. The company is backed by investors including KKR, FTV Capital, Kindred, Notion and 83North.