Lead Data Scientist

About Swap

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.

About the Role

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.

Key responsibilities

• 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.

What we would like to see:

• 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.

Benefits:

• Competitive base salary

• Stock options in a high-growth startup

• Competitive PTO with public holidays additional

• Private Health

• Pension

• Wellness benefits

• Breakfast Mondays

Diversity & Equal Opportunities:

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.