Senior/Lead Data Scientist - Credit

Salary: £48,000 - 70,000 per year

Requirements:

• Deep understanding of transformer architectures and sequence modelling, with the ability to reason through architectural trade-offs
• Hands-on experience designing tokenisation schemes for heterogeneous feature types such as numerical, categorical, and temporal data
• Proficiency in Python, PyTorch, SageMaker, and Airflow
• Experience owning the full model lifecycle, from training through to serving in production
• Comfortable working in a small, high-ownership team on open-ended technical problems
• Experience with Triton kernels or GPU-level optimisation
• Broader ML background spanning areas beyond deep learning
• Experience with large-scale transactional or financial data
• Background in ML infrastructure or MLOps

Responsibilities:

• Work on technically interesting modelling problems in fintech, training large transformer-based models on long sequences of real-world transactional events
• Design tokenisation schemes for numerical, categorical, and temporal features
• Make deliberate decisions about vocabulary size, sequence length, and information compounding
• Work across the full model lifecycle, from data preparation through to production
• Translate research decisions into systems that set the direction for how machine learning operates across our company
• Contribute as part of a small, high-ownership team where your work has genuine impact on the products we ship

Technologies:

• Airflow
• Machine Learning
• PyTorch
• Python
• MLOps

More:

We are a fintech company based in London offering a full-time role with a salary range of 81,425 to 116,438 GBP. We are looking for someone to join a small, high-ownership team working on impactful machine learning systems and large-scale modelling problems. The role involves end-to-end work across research, training, and production, with opportunities to shape how machine learning operates across our products. Candidates should include a CV in English.

last updated 34 week of 2026