The Role

At Zempler Bank, data plays a vital role in how we make better, fairer decisions for our customers and colleagues. As a Data Scientist, you’ll help shape how we use data to protect customers, widen access to credit and create thoughtful, seamless customer experiences all while supporting Zempler Bank’s ambition to grow responsibly and sustainably.

This is a role for someone who enjoys solving meaningful problems, working collaboratively across the business and seeing their ideas make a real‑world difference for both customers and communities.

Why join us?

• You’ll work on problems that matter, helping protect customers and improve financial outcomes
• Your work will be used, not shelved you’ll see your ideas make a difference
• We value inclusive thinking, ethical data use and continuous learning
• You’ll be supported to grow your skills, explore new techniques and shape your career path
• We’re committed to creating a workplace where everyone feels welcome, respected and able to thrive

Hybrid Working

We are very proud to offer one of the most flexible hybrid working arrangements in the industry!

The expectation for this role, will involve a minimum of one day each week - working out of our London Bridge office

Key Responsibilities

Data Interpretations:

• Developing algorithms in Python using both linear and non-linear techniques
• Monitor ongoing performance of algorithms and retrain / redevelop where necessary
• Exploration of new data sources to test whether they can be of value to Zempler Bank
• Implement models into production using tools such as Airflow, PyFlink, BentoML, Git, Jenkins and Octopus

Model Development:

Participate in business projects

Manage the relationship with the model stakeholder

Assist in requirements gathering and project scope definition.

Develop models accordingly.

Coordination – checking in with stakeholders during the Model Development .

Communicate results of model developments effectively to non-technical audience

Qualification, Skills and Experience

Essential:

• Strong Python skills for Data Science
• Good understanding of SQL
• Strong understanding of the mathematical and statistical concepts which underpin Data Science
• Natural curiosity to develop new trains of thought and create new data signals. Driven to understand why things happen
• Ability to work independently and as part of a team

Desirable:

• Working knowledge of interpretability packages such as SHAP
• Experience in developing and applying algorithms within a commercial environment
• Prior experience working with highly imbalanced datasets for binary classification problems
• Event streaming data engineering tools such as Flink or Spark
• Experience with MLOps and tools such as Airflow, BentoML and MLFlow
• Use of Docker
• CI/CD and SDLC (e.g. JIRA, Git, Jenkins, Octopus)