We're looking for a Senior Data Scientist who's passionate about using data to solve real-world problems and has a keen interest in pricing strategy, customer behaviour, and decision science.

In this role, you'll work closely with the Pricing team in OakNorth's Personal Savings business to design experiments, build models, and derive insights that optimise pricing decisions. Your work will directly inform how we price to balance growth and cost-efficiency - helping OakNorth maintain strong customer demand while achieving sustainable funding costs.

This is a high-impact, hybrid role that blends statistical modelling, economic intuition, and stakeholder collaboration, ideal for someone who wants to shape pricing strategy with rigorous analysis and robust experimentation.

The role

• Work in and partner with the Pricing team to understand key challenges around savings pricing, customer acquisition, and retention.
• Analyse historical data and trends to present insights and build models that elevates data insights into the hands of stakeholders.
• Design and evaluate pricing experiments to estimate price elasticity and customer sensitivity across different savings products and customer segments.
• Build and maintain predictive and econometric models to forecast volumes and optimise pricing strategies.
• Identify and test pricing opportunities that balance volume growth with cost of funds, under different market conditions.
• Contribute to tooling and frameworks that support experimentation and analysis at scale.
• Create data products which enables the team to make accurate decisions faster, leveraging AI and automation.
• Collaborate with Data Engineering to ensure the right data is available, structured, and reliable for pricing analytics.
• Communicate results, recommendations, and uncertainty clearly to stakeholders in Product, Finance, and Risk.
• Stay up-to-date on industry trends and pricing techniques, bringing fresh ideas and best practices into the team.

• Ability to apply commercial thinking to data science, focusing on practical outcomes and business impact rather than academic perfection.
• Experience in applied data science, preferably in financial services, pricing, revenue management, or behavioural analytics.
• Strong statistical foundation in regression, experimentation, causal inference, and forecasting.
• Experience with price elasticity modelling, segmentation, and simulation approaches a big plus.
• Strong communication skills - you're able to explain technical concepts and influence decisions.
• Comfortable working with imperfect data, ambiguity, and evolving priorities.
• Bonus: experience with DBT, cloud data warehouses (e.g. BigQuery), or automated experimentation platforms.

• Python (incl. pandas, statsmodels, scikit-learn), Jupyter
• dbt, SQL (BigQuery, PostgreSQL)
• Tableau or similar BI tools
• GitHub, GCP, Docker (optional but useful)

• Collaboration: We work in cross-functional, autonomous squads where product, engineering, and analytics sit together to solve shared problems.
• Outcomes over outputs: We measure success by impact, not volume of work - always tying decisions to business goals.
• Rapid learning & iteration: We experiment early and often, ship fast, and iterate based on what the data tells us.
• Empathy for users: We listen deeply - to both customers and colleagues - and design solutions that work for real people.
• End-to-end ownership: Everyone is empowered to own the work from idea to delivery and beyond.

• We embrace difference and know that when we can be ourselves at work, we are happier, more motivated and creative. We want to be able to bring our whole selves to work, have our own perspectives and know that we belong. As such, through your behaviours at work, we expect you to reflect and actively sustain a healthy engineering environment that looks like this:
• A wide range of voices heard to the benefit of all
• Teams that are clearly happy, engaged, and laugh together
• Perceivable safety to have an opinion or ask a question
• No egos - people listen to and learn from others at all levels, with strong opinions held loosely

• This role offers the opportunity to work closely with the team, requiring a minimum of 3 days per week in the office to foster hands-on collaboration and innovation.
• Work-life balance - 25 days holiday (plus bank holidays) each year, and enhanced family leave allowances.
• Competitive salary & equity - We want people to have a serious stake in the business.
• Good kit - Your choice of the best laptop, running macOS or Ubuntu.
• Team socials - The opportunity to get to know each other outside of work.
• Company socials - A chance to catch up and meet new colleagues weekly over informal office breakfasts and dinners on OakNorth - or at our free barista bar every day.
• Commuter support - We offer the cycle to work & EV scheme.

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