At a Glance
- Tasks: Lead the development of predictive models for credit risk and shape strategic decisions.
- Company: Join Skipton, a mutual organisation dedicated to making life better for our members.
- Benefits: Enjoy flexible working, competitive salary, annual leave, and wellness perks.
- Other info: Embrace a culture of inclusivity and wellbeing at Skipton.
- Why this job: Make a real impact in credit risk modelling while enjoying a supportive team environment.
- Qualifications: Strong knowledge of statistics and experience with large datasets required.
The predicted salary is between 71000 - 71000 £ per year.
Hours
This vacancy is for a permanent full time role, 35 hours per week, working 3 days a week in our Skipton Head Office and two days from home.
Hours
This vacancy is for a permanent full time role, 35 hours per week, working 3 days a week in our Skipton Head Office and two days from home.
- Salary
- £71,000 Per Annum
- Closing Date
Join us at the forefront of credit risk modelling, where you'll lead the development and ongoing evolution of predictive models that help shape strategic decisions and ensure regulatory compliance.
From IRB to IFRS 9, your expertise will be instrumental in assessing credit losses across our residential mortgage portfolio.
What You’ll Do
Your key responsibilities will include
- Extract, analyse and manipulate large datasets to generate meaningful insights and support credit risk modelling.
- Develop, test and document statistical models, ensuring they are robust, reliable and fit for purpose.
- Design and enhance analytical processes that deliver efficient, high-quality business outcomes.
- Champion modelling best practice, governance standards and emerging techniques across the team and wider business.
- Produce and present clear, insightful reporting to stakeholders, including senior management committees.
- Support business change initiatives by providing constructive challenge, driving continuous improvement and adhering to establishe d change management processes.
- What You’ll Need
- Strong knowledge of statistics, predictive modelling techniques and credit risk assessment, including capital and impairment modelling.
- Experience working with large, complex datasets to generate insights and support decision-making.
- Proven experience delivering complex modelling projects and managing stakeholders at all levels, including senior leaders.
- Ability to interpret data, draw meaningful conclusions and translate findings into actionable recommendations.
- Excellent communication skills, with the ability to explain complex technical concepts clearly to both technical and non-technical audiences.
- A self-motivated and proactive approach, with the ability to work independently, manage competing priorities and continuously develop your expertise.
- What’s In It For You
And the way we reward you matters, too.
At Skipton, we offer pay and benefits that really do make life better, together with a genuine thank you for making a difference.
Your work matters.
- Annual discretionary bonus scheme
- 25 days standard annual leave + bank holidays + rising 1 day per year of service to a max of 30 days
- Matching employer pension contribution (up to 10% per annum)
- Colleague Mortgages and access to Skipton products and services at discounted rates
- Flexible working to help balance your commitments
- Private medical insurance, health and wellbeing app, volunteering opportunities, cycle-to-work scheme, discounted gym memberships
- Lifestyle perks such as a Home and Tech voucher, which can be used at John Lewis, Currys, and IKEA
We’re here to make life better for our members.
About Skipton.
Our story began in 1853 in Skipton, North Yorkshire. Today, you’ll find us across England and Scotland, from Aberdeen to Plymouth.
We help over a million members put down roots, save for what matters, and feel good about their money.
As a mutual, they own us, so everything we do is for them.
You'll feel that same fairness and purpose in how all 2,500 of our colleagues work together, too
It all means that life at Skipton is more exciting than you imagine.
- What It's Like To Work Here
- Life at Skipton
We talk and we listen to each other. And we make decisions as a team. That way, you get all the support you need to do work that works for everyone.
For most of our roles there's the option of blended working, which means we mix working from home and meeting in person with three days a week in our Skipton head office and two days working from home.
We also value what everyone brings to Skipton.
And we create a fair place where you can be yourself.
Our colleague networks play a big role in this.
They connect people with similar life experiences and make our workplace warm, friendly, inclusive and welcoming.
It’s not just our members who are important to us.
You are, too.
Lots of organisations talk about wellbeing, but they don’t always back it up.
As a mutual, we put people first.
And that includes the people who work here.
So, when we say we care about your wellbeing, we mean it.
Wellbeing isn't just one thing.
It’s about feeling good, having energy, and being able to be yourself and perform at your best.
That’s why we offer help for your mental and physical health across five key areas.
What’s more, it’s help that you can actually use too - not just read about.
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Model Development Lead in Skipton employer: Skipton Building Society
Skipton Building Society is an excellent employer, offering a vibrant working environment in the heart of Skipton where collaboration and innovation thrive. With a strong focus on work/life balance through hybrid working opportunities, employees benefit from a range of perks including a discretionary bonus scheme, annual leave, and private medical insurance, all while being part of a team that values technical leadership and personal growth.
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We think this is how you could land Model Development Lead in Skipton
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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 Skipton Building Society.
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We think you need these skills to ace Model Development Lead in Skipton
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!
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Craft a Tailored Cover Letter:For a full-time role at Skipton Building Society, 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.
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How to prepare for a job interview at Skipton Building Society
✨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!
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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 Skipton Building Society!
✨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.
