Lead Data Scientist

Swap is the infrastructure behind modern agentic commerce. The only AI-native platform connecting backend operations with a forward-thinking storefront experience.

Built for brands that want to sell anything - anywhere, Swap centralizes global operations, powers intelligent workflows, and unlocks margin-protecting decisions with real-time data and capability. Our products span cross-border, tax, returns, demand planning, and our next-generation agentic storefront, giving merchants full transparency and the ability to act with confidence.

At Swap, we’re building a culture that values clarity, creativity, and shared ownership as we redefine how global commerce works.

As Lead Data Scientist, you will be a senior, highly hands-on contributor responsible for the core intelligence powering Swap’s AI-native commerce platform across multiple product areas. You’ll work end-to-end on complex problems, from pricing and compliance decisions to logistics optimisation, workflow automation, and fraud detection, owning them from discovery through to production impact. You’ll set a high technical bar for data science at Swap: shaping our modelling approaches, experimentation culture, and how we use real-time data to drive decisions. As we scale, you’ll play a key role in how the data science function evolves, including influencing hiring and mentoring others.

• Own the end-to-end data science lifecycle for high-impact problems across multiple product surfaces, from problem framing and data exploration through to deployment and iteration.
• Design, build, and productionise machine learning models for areas as diverse as margin protection, risk and compliance, returns and logistics optimisation, and fraud/risk scoring.
• Lead the development and evaluation of LLM-powered workflow automation (e.g. document understanding, case triage, agentic flows) embedded in merchant and operator-facing tools.
• Define and champion best practices for experimentation, offline/online evaluation to measure impact on conversion, margin, and operational efficiency.
• Collaborate closely with product, engineering, and operations to deeply understand workflows, shape roadmaps, and ship data-driven solutions that solve real merchant problems.
• Partner with data engineering to design and maintain high-quality datasets, features, and pipelines that reliably power models across different domains.
• Act as a senior technical reference point for data science at Swap, helping to set modelling standards, review critical work, and provide guidance to teammates.
• Contribute to the evolution of the data science function over time, including participating in hiring and helping shape how the team operates as we grow.

• Significant experience (typically 6+ years) in applied data science or machine learning roles, with clear ownership of production models that drove meaningful business outcomes.
• Strong hands-on skills in Python and common ML libraries (e.g. pandas, pydantic, scikit-learn, pytorch) plus solid software engineering practices (testing, version control, code review).
• Proven track record in at least one relevant area: fraud/risk modelling, optimisation (pricing, logistics, inventory, returns), or complex e-commerce / cross-border data problems.
• Practical experience deploying and iterating on models in production (ML ops, monitoring, retraining strategies, working with APIs and microservices).
• Familiarity with LLMs and modern NLP techniques (prompting, fine-tuning, retrieval, evaluation) and experience or strong interest in integrating them into real workflows.
• Experience working with large-scale transactional and event data (orders, shipments, payments, customer interactions) and turning it into robust, production-ready features.
• Strong product mindset: comfortable with ambiguity, able to prioritise by impact, and used to collaborating closely with product and engineering in a startup environment.
• Interest in helping shape a high-performing data science function over time through mentorship, technical leadership, and involvement in hiring.

• Competitive base salary
• Stock options in a high-growth startup
• Competitive PTO with public holidays additional
• Private Health
• Pension
• Wellness benefits
• Breakfast Mondays

We embrace diversity and equality in a serious way. We are committed to building a team with a variety of backgrounds, skills, and views. The more inclusive we are, the better our work will be. Creating a culture of equality isn't just the right thing to do; it's also the smart thing.