Data Scientist

About the role

Kroo Bank is building the next generation of banking with a strong focus on technology, data, and innovation. As a digital-first bank, it uses data science to make better decisions, improve customer outcomes, and create products that people trust and enjoy.

Because fintech changes quickly, this position offers the chance to apply advanced analytics, machine learning, and experimentation to meaningful business problems. You will collaborate with teams across Product, Risk, Operations, Compliance, and Engineering to drive smarter use of data across the organisation.

In this role, you will design, assess, and deploy data science solutions that improve decision-making and customer experience. Your work will support high-impact areas such as credit risk, fraud prevention, customer engagement, and operational efficiency through strong analysis, modelling, and experimentation.

Key responsibilities

• Create and refine statistical and machine learning models to tackle business challenges in areas such as credit risk, fraud, customer engagement, and operational efficiency.
• Work with stakeholders to shape problem statements, define success measures, identify data needs, and outline practical delivery plans.
• Explore datasets and engineer features to identify outcome drivers and improve model quality and explainability.
• Design solid evaluation approaches, including baseline comparisons, validation methods, monitoring metrics, and performance reporting.
• Help move models into production with Engineering, contributing to reusable pipelines and clear model documentation.
• Track production models, spot performance drift, suggest improvements, and assist with retraining or recalibration when needed.
• Use probability and statistical inference to design experiments, interpret outcomes, and present recommendations clearly.
• Strengthen data quality by flagging issues, supporting cleaning and standardisation efforts, and helping define reliable data practices.
• Write clean, testable Python code using standard data science tools and follow engineering practices suited to production environments.
• Use SQL and dbt to pull, transform, and validate data for analysis and modelling while maintaining traceability and reliability.
• Partner with Risk, Compliance, and Audit teams to ensure work is well governed, documented, and aligned with regulatory expectations.
• Contribute to ongoing improvements in data science methods, tooling, and team processes.

Requirements

• Hands-on experience creating and assessing statistical and machine learning models in a commercial setting.
• Strong analytical and problem-solving ability, with the skill to turn business needs into practical data science solutions.
• Capability to define and source datasets independently, working with stakeholders to confirm data requirements, coverage, and traceability.
• Ability to clean data effectively, identify data issues proactively, and help improve data reliability and standards.
• Comfort with exploratory analysis and statistical investigation, and the ability to turn findings into actionable insights.
• Solid Python programming fundamentals, with experience producing maintainable code, using tests, and documenting shared work.
• Experience using SQL and dbt for extracting, transforming, validating, and analysing data.
• Ability to build clear visualisations and model summaries for both technical and non-technical audiences.
• Strong communication skills, including the ability to explain complex analytical ideas in a simple and audience-appropriate way.
• Excellent attention to detail, with an emphasis on reproducible, validated, and well-documented work.
• Ability to manage projects well, deliver to deadlines, handle competing priorities, and support effective team delivery.
• Useful experience working with Product, Risk, Operations, Compliance, and Engineering teams.
• Helpful awareness of model governance, risk management, and regulatory requirements in financial services.

Benefits

• Flexible hybrid working: the London office is available as a collaboration space, and candidates should expect to be onsite 1–2 days per week on a regular basis.
• A workplace that actively supports diversity, equity, and inclusion, with respect and support for every employee.
• Reasonable adjustments are available throughout the recruitment process for candidates who need them.

Agency and application notes

Unsolicited agency resumes are not accepted, and the company will not be responsible for any fees linked to resumes submitted without request. Candidates are expected to apply directly through the advertised application route rather than contacting the company or its employees by email, LinkedIn, or other channels for status updates or enquiries.