Data Science Manager

In this role you lead and shape Royal Mail’s Data Science capability, blending hands-on analytics with people leadership to deliver ML, forecasting and AI solutions that drive customer experience and operational improvements. You’ll mentor data scientists, set best practices, and partner with business and engineering teams to scale impact across a large, transformation-driven organisation. This is a chance to steer high-impact analytics in a modern, data-driven environment.

• car allowance
• healthcare
• up to 18% annual bonus
• 25 days annual leave plus bank holidays
• CDC pension scheme with 12%+ contributions
• family friendly support

• Lead design and delivery of advanced Data Science, ML and AI solutions for strategic and operational decision-making
• Provide technical leadership, coaching and mentoring to Data Scientists
• Drive adoption of data science best practices, standards and modern ways of working
• Collaborate with Data Engineers, ML Engineers and Technology teams to build scalable solutions
• Partner with business stakeholders to identify opportunities and shape data-driven approaches
• Oversee solution quality, methodology selection and delivery across the portfolio
• Support recruitment and capability development of the Data Science function
• Translate analytical outputs into practical business recommendations with measurable value

• Significant experience delivering advanced analytics, ML and optimization solutions in a commercial setting
• Strong expertise in statistical modelling and experimental design
• Advanced Python and SQL skills
• Experience leading complex Data Science initiatives from problem definition to value realization
• Proven coaching/mentoring of Data Scientists
• Strong stakeholder management and ability to influence technical and non-technical audiences
• Experience with large, complex datasets to generate actionable insights
• Knowledge of cloud-based analytics platforms and modern ML deployment practices
• Passion for innovation, continuous improvement and developing data science capability

• stakeholder management
• leadership and people development
• communication of complex outputs to non-technical audiences
• Python
• SQL
• Machine Learning techniques