Contract type: Permanent
Location: London
Working style: Hybrid 50% home/office based
We're excited to be hiring a brand new Senior Process Analyst to join our Data & AI Transformation team at Royal London Asset Management, supporting our journey to become a more data and AI-enabled organisation.
This is a fantastic opportunity to help shape the future of how we work. You'll partner with colleagues across the business to understand, redesign and improve processes, using data, automation and emerging AI capabilities to deliver meaningful business outcomes. Working closely with stakeholders, AI strategists and delivery teams, you'll uncover opportunities for improvement, map complex processes and help design scalable future-state solutions that create lasting value.
We're looking for someone who combines strong process analysis and stakeholder engagement skills with a passion for continuous improvement and innovation. Experience within asset management or financial services is valuable, as is an interest in how technology, automation and AI can help simplify processes, enhance efficiency and improve colleague and customer experiences.
About the role
Process Reinvention Delivery
- Lead process reinvention initiatives with minimal supervision.
- Own discovery activities including process mapping, analysis and stakeholder interviews.
- Identify and solve complex process challenges, leveraging data, automation and AI.
Process Design & Methods
- Apply process design, service design and process mapping methodologies consistently.
- Contribute to the development and continuous improvement of process reinvention standards, methods and best practice.
Stakeholder Collaboration
- Partner with stakeholders to understand challenges and identify improvement opportunities.
- Facilitate workshops, discovery sessions and design-thinking activities.
- Build strong relationships across Operations, Technology and Data & AI teams.
Capability Building & Continuous Improvement
- Enhance process reinvention tools, templates and guidance.
- Support knowledge sharing and capability development across the business.
- Stay current with process improvement, automation and AI trends
About you
- Experience in a relevant Asset Management or Financial Services role, with exposure to process improvement, change initiatives, process mapping, analysis and documentation.
- A good understanding of data-led process improvement, performance metrics, automation and AI-enabled approaches, with a proactive interest in process, data and AI.
- Strong analytical and problem-solving skills, with clear written and verbal communication and strong attention to documentation quality standards.
- Able to collaborate effectively with business and delivery teams, work with some ambiguity under guidance, and operate with confidence and autonomy.
- Organised, delivery-focused and able to manage your own workload effectively.
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, Trustworthy, 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.