Data Scientist in Northampton

Data Scientist in Northampton

Northampton Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Create predictive credit risk models and analyse complex datasets to enhance lending decisions.
  • Company: Billing Finance, a family-owned vehicle financing company focused on customer-centric solutions.
  • Benefits: Discretionary bonuses, hybrid working, private medical, and personal growth fund.
  • Other info: Exciting opportunity for career growth in a supportive and innovative environment.
  • Why this job: Join us in transforming the credit risk landscape and make a real impact on customer journeys.
  • Qualifications: Experience in Python, SQL, and statistical modelling; strong analytical and presentation skills.

The predicted salary is between 60000 - 80000 £ per year.

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?

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:

  • Develop 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.
  • Work with large and complex datasets to identify opportunities that improve lending decisions, enhance customer outcomes and support sustainable portfolio growth.
  • Combine traditional data science techniques with practical commercial application, leveraging modern analytics, machine learning and AI-assisted development tools to accelerate model development, improve decision making and deliver tangible business value.
  • Collaborate with stakeholders across Credit Risk, Operations, Finance, Collections and Technology to deliver innovative, data-driven solutions that support the company's strategic objectives.
  • 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 not 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).
  • Identify and analyse causes of urgent defects and make predictions on likelihood of recurrence.
  • Act as an internal consultant to the business on data driven decision making and insights.
  • Develop differentiated pricing models and educate stakeholders on findings.
  • Discover trends and patterns within complex data and present findings to stakeholders.
  • Leverage state-of-the-art data mining and machine learning tools and methodologies to drive improved business decisions.
  • Document and articulate key learnings from the data mining exercises.

Your Working Style and Experience:

You're proactive with excellent stakeholder management 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
  • Hybrid working
  • Employee Assistance Programme
  • Annual £200 personal growth fund
  • Paid volunteering days

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.

Data Scientist in Northampton employer: Billing Finance

AJ Mackaness is an excellent employer that values its employees and fosters a supportive work culture. Located in Billing, Northamptonshire, we offer flexible working arrangements, a range of benefits including a discretionary bonus scheme and personal growth fund, and opportunities for professional development within our small, friendly team. Join us to enjoy a fulfilling career in a family-run business that prioritises employee well-being and community engagement.

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Contact Details:

Billing Finance Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Scientist in Northampton

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Billing Finance!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Scientist at Billing Finance.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Billing Finance.

Apply Directly through Our Website

When you find a suitable opening like Data Scientist at Billing Finance, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Data Scientist in Northampton

Credit Risk Modelling
Predictive Modelling
Machine Learning
Data Analysis
Statistical Modelling Techniques
Python
SQL

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Billing Finance, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Billing Finance. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Billing Finance

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Billing Finance!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.