We are recruiting for the newest member of our Data Science team. If you have a passion for using advanced analytics and data science to drive data‑informed decisions, then this could be the role for you.
The Lead Data Scientist is a pivotal role, where you’ll be responsible for using advanced analytics and data science to promote data-led decision making across the Society. You’ll provide thought leadership to a range of stakeholders and take a proactive approach to encouraging the right outcomes from your analysis.
You’ll use your experience to identify opportunities and make recommendations that deliver return on investment, improve customer engagement, and support more efficient running of the organisation.
As a senior member of our Data Science team, you’ll mentor and support colleagues to deliver our data and analytics strategy. You’ll balance being hands‑on with data with being a key contact and role model for the wider team.
Who Are We?
Not just another building society. Not just another job.
We're the fourth biggest building society in the UK, and what makes us different is that we're a mutual organisation. We don't have shareholders; we're owned by our members.
Our colleagues say Skipton is a great place to work — and you could be one of them, bringing fresh ideas on how we can continue to keep customers at the heart of what we do.
Whatever your background and whatever your goals, we’ll help you take the next step towards a better future.
You will also be joining us at an exciting time for our Data Capability function. Our aspiration is to create a single, joined‑up Data and Intelligence platform where everything related to data sits in one place, enabling clear ownership, better decision‑making and full end‑to‑end control of the data lifecycle. To achieve this, we are bringing together the core elements of our data capability: reporting (what’s happening), analytics (why it’s happening), data science (what’s likely to happen next), data governance (how we work safely, consistently and responsibly) and data engineering.
What’s In It For You?
Skipton values work/life balance, and we’re proud to support hybrid and flexible working where possible. Our newly refurbished head office offers a vibrant and collaborative workspace.
We have a range of other benefits available to you including:
Annual discretionary bonus scheme
25 days’ standard annual leave plus bank holidays, increasing by one day per year of service up to 30 days
Holiday trading scheme, allowing you to buy or sell annual leave
Matching employer pension contributions (up to 10% per annum)
A strong commitment to training and development
Private medical insurance for all colleagues
Salary sacrifice electric/hybrid car scheme
Three paid volunteering days per year
Diverse and inclusive colleague networks, including our Carers and Pride Alliance groups
A wide range of wellbeing initiatives, including our cycle‑to‑work scheme and discounted gym membership
What Will You Be Doing?
You’ll be responsible for analysis and statistical/machine‑learning modelling to drive value and deliver both complex and smaller projects focused on commercial performance, strategic alignment and practical impact. Alongside generating insights, you’ll foster a culture of analytical curiosity by asking the right questions to fully understand and deliver business needs.
You’ll work closely with leaders across the organisation, building and maintaining strong relationships to ensure your analysis resonates with your audience. Through coaching and mentoring, you’ll also support the development of your team.
You’ll play a key role in migrating our models and processes from on‑premise technology to a cloud‑based analytics platform.
What Do We Need From You?
We’re looking for someone with extensive experience across a broad range of data science techniques, using data‑coding languages and analytics software. You’ll also be confident in communicating findings and recommendations to stakeholders and in sharing your knowledge with others.
Key competencies for this role include:
Solid experience applying data‑driven mathematical, statistical and machine‑learning models using Python and/or R
Exposure to distributed processing systems for big data workloads (e.g., Microsoft Azure)
Experience managing large and complex datasets using SQL
A proven track record of translating business problems into analytical solutions
Strong presentation, communication and influencing skills, with the ability to tailor your approach to different audiences and simplify complex concepts
Experience mentoring junior data scientists and reviewing their work
Experience working in a commercially focused environment