Senior Applied Data Scientist

ABOUT US

We’re the world’s leading provider of secure financial messaging services, headquartered in Belgium. We are the way the world moves value – across borders, through cities and overseas. No other organisation can address the scale, precision, pace and trust that this demands, and we’re proud to support the global economy.

We’re unique too. We were established to find a better way for the global financial community to move value – a reliable, safe and secure approach that the community can trust, completely. We’re always striving to be better and are constantly evolving in an ever-changing landscape, without undermining that trust. Five decades on, our vibrant community reflects the complexity and diversity of the financial ecosystem.

We innovate diligently, test exhaustively, then implement fast. In a connected and exciting era, our mission has never been more relevant. Swift now has a presence in 200+ countries and legal territories to serve a community of more than 12,000 banks and financial institutions.

You are applying for an Applied Data Scientist position in the team that has access to one of Swift’s most valuable assets: its data. Your mandate is to find innovative ways of leveraging that data, either to support the strategy of the company or to design new data-driven insight or solutions for our customers. How? By leveraging AI and data science techniques.

As an applied data Scientist you will be involved in topics including anomaly detection, predictive modelling, synthetic data generation and exploring the opportunities of generative AI. The financial industry is a fast-moving environment as emerging firms are making inroads into critical financial services. This fast‑paced evolution is reshaping financial services providing consumers with new, convenient options while challenging established norms.

Swift has a unique position in the global financial ecosystem, meaning you will have the opportunity to design services that have a global impact and high added value for our customers.

The team you will be joining is composed of Applied Data Scientists and Automation experts working in the Ai, Analytics and Automation Tribe.

• Lead the design, development, and execution of advanced statistical models and machine learning algorithms to solve complex business problems and derive actionable insights from large datasets.
• Collaborate closely with cross‑functional teams to define and refine business requirements, ensuring data‑driven solutions align with organizational goals and have measurable impact.
• Own the full lifecycle of data science projects, from ideation and data collection through to deployment, ensuring scalable, high‑quality solutions.
• Provide technical leadership and mentorship to junior team members, fostering a culture of innovation, continuous learning, and collaboration within the data science community and the AI, Analytics and Automation tribe.
• Proactively engage with stakeholders at various levels, delivering clear, compelling presentations, and effectively communicating complex technical findings to non‑technical audiences.
• Champion best practices in data science and machine learning across the organization, promoting knowledge sharing and driving the continuous improvement of methods and processes.
• Ensure that proposed data science solutions comply with internal governance and compliance standards, adapting to evolving business needs while maintaining flexibility and efficiency.

• Expert‑level proficiency in Python with deep knowledge of its data science ecosystem (e.g., Pandas/Polars, Num Py, scikit‑learn, PyTorch).
• Proven experience in designing, building, and deploying robust analytics pipelines that are scalable, efficient, and deliver value.
• Strong background in machine learning/AI, with hands‑on experience using advanced models and frameworks across supervised, unsupervised learning, and deep learning.
• Expertise in version control systems (e.g., Git) and experience working with CI/CD pipelines and software development best practices.
• Extensive experience in managing the end‑to‑end lifecycle of data science projects, ensuring timely…