Junior Data Scientist - Fraud & AML Monitoring

At M&G, our purpose is to give everyone real confidence to put their money to work. With a heritage dating back more than 175 years, we have a long history of innovation in savings and investments, combining asset management and insurance expertise to offer a wide range of solutions.

Our two distinct operating segments, Asset Management and Life, work together to provide access to balanced, long-term investment and savings solutions.

Through telling it like it is, owning it now and moving it forward together with care and integrity; we are creating an exceptional place to work for exceptional talent.

We will consider flexible working arrangements for any of our roles and offer workplace adjustments to ensure you have the support you need to succeed in your role.

This is an outstanding opportunity to join the Fraud Monitoring and Analysis team within M&G's Operational Planning Centre of Excellence. The role is open to graduates, career starters, and internal colleagues who are looking to build or develop a career in Data Science, Analytics, and Financial Crime.

You do not need to be a fully-formed expert. Instead, we are looking for someone with a strong natural aptitude for data, a solid technical foundation and an intuitive ability to use data for real-world insights to prevent financial crime by identifying risks early on. You will receive excellent support, mentoring, and exposure to modern cloud-based architectures, whilst working on fraud and AML challenges.

The team is a key part of M&G's Financial Crime Enhancement Programme, a major transformation initiative bringing significant change, expansion, and opportunities to collaborate with multiple teams across the business.

• Ideal for graduates or first-time data scientists
• Excellent technical development and upskilling support
• Strong opportunity for internal colleagues looking to reskill or progress
• Broad exposure to fraud, AML, technology, operations, and senior stakeholders
• High visibility role offering excellent networking opportunities
• Opportunity to work within a recognised Centre of Excellence
• Exposure to large-scale change and transformation initiatives

• Working across the full solution lifecycle, you will:
• Design and build solutions that enable the delivery of fraud and anti-money laundering monitoring capability across our business
• Be the team expert on Azure Databricks, and support other team members in upskilling in this area
• Be the team expert on Power BI, and support other team members in upskilling in this area
• Support the teams wider activities, assisting in investigation of suspicious transactions from a data standpoint
• Understand how complex data sources connect, to build in automation and to develop a capability to successfully isolate suspicious transactions and behaviours
• Seek out new sources of data, which can be linked to online/offline transactional or customer data to provide new or enhanced insight to the business
• Understand and review how other parts of the business are using data and data tools to see how we can learn, evolve and align
• Build scalable and repeatable solutions that can be introduced in new areas/journeys/products, in line with our focus on building a centre of excellence
• Conduct ongoing data quality assessments to ensure the necessary data is continuously ingested into the appropriate tools/applications that facilitate our transaction monitoring capabilities. This also includes the assessment of the accuracy of the data
• Joining data from multiple sources (Data modelling)
• This is an individual contributor profile wherein the candidate is required to work in collaboration with the team Design and build systems that mine massive datasets and structure/ engineer it to be usable
• As part of a Centre of Excellence, you will help develop best practice that can be shared across M&G.

• A strong interest in data, analytics, and financial crime
• Proven experience translating business problems into analytical solutions
• Confidence working with Fraud, Compliance, Technology, and Operations…