Data Scientist

Billing Finance Limited; Northampton; On-site; GBP 70,000 - 100,000; Full time

Benefits offered by this job

Discretionary bonus scheme

Private Medical

Pension salary sacrifice

Income Protection

Employee Assistance Programme

Job summary

Billing Finance Limited is seeking a Data Scientist to help establish our data science and credit risk modelling capability. You will develop predictive credit risk models and work with large datasets to improve lending decisions and portfolio growth.

You will collaborate with diverse teams to translate business questions into analytical solutions, utilising Python, SQL, and cloud tools to deliver actionable insights and robust governance.

Qualifications

• Strong in Python and SQL with solid statistical modelling and predictive analytics experience.
• Experience communicating complex data insights to non-technical stakeholders.
• Background in credit risk, lending or fintech is preferred.

Responsibilities

• Develop predictive credit risk models including PD, LGD and EAD.
• Create robust model documentation, validation and governance materials.
• Collaborate with Credit Risk, Operations and Finance to implement analytics solutions.
• Build visualisations and presentations for technical and non-technical audiences.

Skills

Python

SQL

Statistical modelling

Predictive analytics

Stakeholder management

Tools

BigQuery

Google Cloud

Job description

• Are you a Data Scientist who's worked within a credit risk, lending, banking, fintech or consumer finance environment previously?
• Can you create compelling reports that tell a story and explain complex data sets to all audiences?
• Do you have the experience and drive to help establish and develop our data science and credit risk modelling capability from the ground up?

About the Role.

We're looking for a highly skilled and motivated Data Scientist to join us during an exciting time of Change and Transformation.

Reporting to the Credit Risk Manager and working closely with the Director of Credit Risk and Data Analytics, this is a unique opportunity to become one of the key architects of our future decisioning and risk management framework.

What You’ll Do.

You’ll be responsible for developing our first generation of predictive credit risk models, including Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD), application scorecards, affordability models and collections strategies.

You will work with large and complex datasets to identify opportunities that improve lending decisions, enhance customer outcomes and support sustainable portfolio growth.

Combining traditional data science techniques with practical commercial application, you’ll leverage modern analytics, machine learning and AI-assisted development tools to accelerate model development, improve decision making and deliver tangible business value.

You’ll collaborate with stakeholders across Credit Risk, Operations, Finance, Collections and Technology to deliver innovative, data-driven solutions that support the company’s strategic objectives and will use your quantitative skills to deliver actionable insights to a variety of senior external and internal stakeholders.

Responsibilities

• Design, develop, validate and monitor predictive credit risk models including but limited to ECL, pricing, forecasting and provisioning models.
• Maintain application scorecards, affordability models and decisioning strategies that support responsible lending and portfolio growth.
• Support the development of provisioning, forecasting and portfolio monitoring methodologies.
• Analyse customer, bureau, affordability and behavioural data to identify trends, risks and opportunities.
• Utilise machine learning and AI-assisted development techniques to accelerate model development and improve analytical efficiency.
• Produce robust model documentation, validation reports and governance materials.
• Work closely with Credit Risk, Operations, Transformation and Finance teams to translate business problems into analytical solutions.
• Build scalable analytical processes using BigQuery, Python and Google Cloud technologies.
• Develop clear and insightful visualisations and presentations for both technical and non-technical audiences.
• Stay informed of industry best practice, emerging technologies and regulatory developments relevant to consumer credit risk modelling.
• Collaborate with stakeholders across departments to understand their data needs and deliver tailored solutions.
• Ensure data integrity and compliance with relevant regulations (e.g., GDPR).
• Identifying and analysing causes of urgent defects and making predictions on likelihood of recurrence
• Acting as an internal consultant to the business on data driven decision making and insights
• Developing differentiated pricing models and educating stakeholders on findings
• Discovering trends and patterns within complex data and present findings to stakeholders
• Leveraging state-of-the-art data mining and machine learning tools and methodologies to drive improved business decisions
• Documenting and articulate key learnings from the data mining exercises

Your Working Style and Experience.

You’re proactive with excellent stakeholder managements skills, a confident presenter and someone who stays informed about emerging technologies and methodologies.

You’ve experience of using Python, a strong knowledge of SQL, a solid understanding of statistical modelling techniques and predictive analytics, and experience developing, validating or monitoring predictive models and scorecards.

About Billing Finance

We are a privately-run family owned vehicle financing Company based on the outskirts of Northampton. We focus on customers with non-standard credit profiles that may not fit the automated underwriting processes of other lenders. Our mission is to help get all our people, including customers and staff “ where they need to be ” by “ putting them at the heart of everything we do ” . We are entering an exciting phase of transformation and as a small company, this role will offer the successful candidate the opportunity to work across the whole customer journey cycle, and to directly see the impacts that they made.

Our values are:

• We are responsible – We are conscious of our impact on people and planet
• We care about you – We are kind and compassionate with our customers and with each other
• We work with you – We support financial wellbeing for our customers and the wider community

The successful candidate will not only have a successful and fulfilling career with us but will also receive a fantastic range of benefits:

• Discretionary bonus scheme
• Electric Vehicle salary sacrifice scheme
• Pension salary sacrifice scheme
• Private Medical
• Income Protection
• Employee Assistance Programme

The Recruitment Process and How We Will Use Your Data

The recruitment process will involve obtaining information and/or exchanging it with the following organisations to assist with our pre-employment checks prior to interview.

• Credit Reference Agencies – to complete a soft credit check to understand your financial history
• CIFAS – to check both National and Internal databases for fraudulent activity. The personal information we have collected from you will be shared with Cifas who will use it to prevent fraud, other unlawful or dishonest conduct, malpractice, and other seriously improper conduct. If any of these are detected, you could be refused certain services or employment. Your personal information will also be used to verify your identity. Further details of how your information will be used by us and Cifas, and your data protection rights, can be found here https://www.cifas.org.uk/fpn .

To complete these checks, you will be asked to provide your address history for the past six years, along with your full name and date of birth.

The successful candidate will be required to undergo a Basic DBS check to comply with our FCA compliance framework. A satisfactory Basic Disclosure showing no unspent convictions is a prerequisite for this position.

We may also ask for proof of your right to work status or evidence of any qualification or experience prior to being offered employment. Further information on how we collect and use your data during the recruitment process can be found in our Privacy Policy here https://billingfinance.co.uk/privacy-policy/

Billing Finance is an equal opportunities employer, and we understand that for some candidates to perform their best they may need some reasonable adjustments. If we can make your application journey with us more suitable for you, please do let us know and we will endeavour to help.