Remote opportunity at
PaddleHead of Data Science
Paddle operates as a Merchant of Record for digital product companies, helping them handle payment infrastructure, compliance, subscriptions, and pricing context across thousands of global software…
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About This Role
Paddle operates as a Merchant of Record for digital product companies, helping them handle payment infrastructure, compliance, subscriptions, and pricing context across thousands of global software businesses. The company is backed by investors such as KKR, FTV Capital, Kindred, Notion, and 83North. To expand its capabilities, Paddle seeks a Head of Data Science to establish the data science function from scratch. This is a foundational, hands-on role where the initial…
Job Description
Paddle operates as a Merchant of Record for digital product companies, helping them handle payment infrastructure, compliance, subscriptions, and pricing context across thousands of global software businesses. The company is backed by investors such as KKR, FTV Capital, Kindred, Notion, and 83North. To expand its capabilities, Paddle seeks a Head of Data Science to establish the data science function from scratch.
This is a foundational, hands-on role where the initial focus involves building rather than managing. Operating as the sole member of the function during the early stages, the professional will write code in Python and SQL, engineer features, evaluate models and agents, and deploy systems into production alongside engineering teams. Responsibilities span automated decision-making within the product, covering traditional machine learning and agentic systems across payment performance, revenue recovery, sales, marketing, growth, monetisation, risk, and compliance. Over time, the role will involve recruiting and leading a hub-and-spoke team embedded across key business areas.
Responsibilities
- Prioritize value-based use cases across payment performance, revenue recovery, sales operations, marketing, growth, monetisation, risk, trust, and compliance, refreshing the backlog quarterly
- Personally deliver the first system end-to-end, including analysis, back-testing, feature engineering, modeling, deployment, and A/B testing
- Operate deployed systems by managing monitoring, retraining, drift response, incident handling, and rollbacks alongside engineering teams
- Work across traditional machine learning models and agentic systems using tools, evaluations against golden answer sets, and trace-level observability
- Hire, mentor, and lead senior data scientists and machine learning engineers within a hub-and-spoke structure
- Collaborate with the Data Platform and Engineering teams to establish a production stack featuring reproducible training data, model registries, and inference services
- Measure financial impact through shadow and A/B testing, publishing a quarterly report on realised value co-signed by Finance
- Define governance models for automated decision-making in partnership with Legal, Privacy, Compliance, and Risk
- Embed directly within cross-functional delivery groups consisting of product owners, domain experts, and platform engineers
Requirements
- Experience leading data science or machine learning teams that own production systems which measurably moved commercial metrics
- Current hands-on technical proficiency in writing SQL and Python, engineering features, and evaluating models and agents
- Practical background spanning both traditional machine learning and agentic systems
- Experience operating live systems through monitoring, retraining, incident response, and on-call duties
- Strong foundation in experimentation, uplift modeling, and back-testing with financial validation
- Familiarity with production infrastructure such as training pipelines, model registries, inference services, feature stores, and drift detection
- Background in payments, fintech, subscriptions, high-volume commercial operations, or another regulated transactional domain
- Familiarity with regulated machine learning constraints including model risk assessments, data protection impact assessments, auditability, and traceability
Core Skills
Benefits
- Attractive salaries
- Stock options
- Unlimited holidays
- Enhanced parental leave
- Retirement plans
- Private healthcare
- Well-being initiatives
- Annual learning fund and constant exposure to new challenges
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
What is the remote work policy for this role?
Paddle operates as a digital-first company, giving employees the freedom to choose where, when, and how they work within designated hub locations. The available hub locations for this role are shared in the job description.
What is the employment type?
The position is a full-time employment opportunity.
What is the salary for the Head of Data Science?
The source posting does not specify the salary for this role.
Who will this position report to?
The Head of Data Science reports directly to the VP of Data.
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