Data Scientist

Junior Data Scientist

Department: Credit Risk

Location: Hybrid – 3 days in office

About My Client

My client is a forward-thinking financial services organisation that believes everyone should have the ability to access, understand, and manage their money with confidence. The company’s mission is to empower individuals to make smarter financial decisions through data-driven insight, innovative technology, and clear communication.

Although still in a growth phase, my client has assembled a highly capable team and is committed to achieving ambitious goals in the years ahead. Their products are designed to simplify money management, enabling customers to gain greater control and flexibility in their financial lives.

About the Role

The organisation has an established model framework but remains agile in exploring new ways of working and thinking. The Junior Data Scientist will support a range of initiatives focused on leveraging data to drive business performance, enhance customer experience, and improve operational efficiency.

This role primarily supports credit risk initiatives, ensuring the company delivers against its annual objectives while maintaining a strong customer focus. The successful candidate will contribute to the development and execution of the credit risk roadmap and assist in prioritising tasks to ensure successful delivery.

Key Responsibilities

Model Development and Implementation

• Develop predictive models across key areas such as credit decisioning, fraud detection, and customer segmentation.
• Ensure data integrity and quality through robust validation and auditing processes.
• Evaluate and document scorecard effectiveness, monitoring performance to ensure ongoing relevance and compliance.

Analytics

• Design and conduct experiments to test hypotheses and inform decision-making, defining expected outcomes and tracking results.
• Analyse processes and customer journeys to identify measurable improvement opportunities.
• Highlight areas where modelling can create uplift in decision quality, efficiency, or cost-effectiveness.
• Investigate new data sources and methodologies to enhance customer decisioning and experience.

Controlling Credit Risk

• Propose, monitor, and analyse credit decisions with consideration for regulatory standards and customer outcomes.
• Assess performance against expectations, ensuring adherence to risk appetite and compliance requirements.
• Work closely with commercial teams to define appropriate pricing and limits based on risk and return principles.

Regulatory Compliance and Consumer Duty

My client expects all team members to take personal responsibility for ensuring the best outcomes for customers. This includes adhering to regulatory conduct rules such as:

• Acting with integrity.
• Demonstrating due skill, care, and diligence.
• Maintaining openness and cooperation with regulators.
• Treating customers fairly and with respect.
• Upholding proper standards of market conduct.

About the Candidate

Approach

• A self-motivated professional with a natural curiosity for understanding how systems and processes interconnect.
• Comfortable working independently and collaboratively across teams.
• Adaptable and proactive within a dynamic, growing business environment.
• Solution-focused with a strong drive to enhance customer experience and business performance.

Ways of Working

• Contribute to structured processes that simplify onboarding and team efficiency.
• Share knowledge and maintain clear, accessible documentation.
• Proactively automate repetitive tasks to increase analytical capacity and impact.

Qualifications and Experience

• Experience working with multiple data sources (knowledge of bureau and open banking data advantageous).
• Foundational understanding of credit card operations.
• Strong coding proficiency, with a focus on structure and automation.
• Skilled in developing insightful management information (MI) and presenting data-driven narratives.
• Effective time management and prioritisation skills.
• Experience with Python (required), SQL, and Power BI.
• Practical experience with XGBoost and logistic regression models (minimum).

Benefits

• Private Medical Care: Access to premium healthcare services.
• Health Cash Plan: Contributions toward everyday medical expenses, including digital physio and skin clinic access.
• Gym Discounts: Reduced memberships across various fitness providers.
• Life Assurance: Coverage at four times annual salary.
• Pension Scheme: 3% employer and 5% employee contribution.
• Annual Leave: 25 days per year, plus options to buy or sell up to 5 days.
• Additional Leave: Birthday leave and 5 volunteering days annually.
• Employee Assistance Programme: Holistic wellbeing and mental health support.
• Learning and Development: Continuous professional growth opportunities.