Process Reinvention Lead




Contract type: Permanent


Location: London


Working style: Hybrid 50% home/office based




Role purpose



Lead the Data & AI Process Reinvention capability, with line management of a small team, and support RLAM's end-to-end process transformation across priority AI first areas. You will work closely with business colleagues to diagnose inefficiencies, redesign operating processes and drive measurable improvements, ensuring processes are fundamentally rethought before automation is applied. Using a structured, consultative approach, you will enable scalable outcomes through data, automation and AI, while establishing clear ways of working and quality expectations.




About the role:

• Lead end-to-end process transformation initiatives, from discovery through to implementation and adoption. This means to

• Diagnose current-state processes, identify inefficiencies and root causes, and design scalable future-state solutions

• Apply structured problem-solving techniques (e.g. value stream mapping, root cause analysis) to drive clear, actionable outcomes

• Identify and enable opportunities to leverage data, automation and AI, ensuring solutions are scalable and integrated

• Challenge existing ways of working, ensuring processes are redesigned before automation is applied

• Recommend how the transformation would deliver measurable business benefits, including efficiency, control and scalability improvements

• Facilitate workshops and engage stakeholders to align on problems, solutions and outcomes

• Communicate insights and recommendations clearly to both technical and non-technical audiences

• Build and manage a pipeline of process improvement opportunities, prioritised by value, risk and feasibility

• Contribute to developing repeatable methods, standards and best practice for process reinvention

About you:

• Experience in process transformation, operational excellence, consulting or change delivery, ideally within financial services or asset management

• Strong process mapping, analysis and future-state design skills, with a structured problem-solving approach

• Understanding of how process redesign links to data, automation and AI, with the ability to identify practical use cases

• Proven ability to lead workshops, challenge thinking and engage stakeholders across business and technology teams

• Able to prioritise and manage multiple initiatives, focusing on delivering measurable business value

• Strong communication skills, translating complex problems into clear, actionable recommendations

• Experience working across operating model, process and technology change initiatives

• Comfortable influencing outcomes and driving adoption of new ways of working

• Exposure to process mining, automation or AI-enabled transformation is beneficial

• Coaching or team leadership experience is an advantage

About Royal London Asset Management



Royal London Asset Management (RLAM), part of the Royal London Group, is one of the UK's leading fund management companies working with a wide range of clients across the globe to achieve their investment goals. Our long-term, client-driven focus means that we have a long-standing commitment to responsible investment. We act as responsible stewards of our clients' capital, exercising their rights and influencing positive change.



Our People Promise to our colleagues is that we will all work somewhere inclusive, responsible, enjoyable and fulfilling. This is underpinned by our Spirit of Royal London values; Empowered, Trustwrthy, Collaborate, Achieve.



We've always been proud to reward employees by offering great workplace benefits such as 28 days annual leave in addition to bank holidays, an up to 14% employer matching pension scheme and private medical insurance.




Inclusion, diversity and belonging



We're an inclusive employer. We celebrate and value different backgrounds and cultures across Royal London. Our diverse people and perspectives give us a range of skills which are recognised and respected - whatever their background.



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