Senior Manager, Risk Appetite and Analytics

Lloyds Banking Group
Edinburgh
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Staff Data Engineer

Senior Data Analyst - HOTH

Senior Staff Data Engineer

Senior Data Analyst - HOTH, Permanent

Senior Data Analyst

Manager – Data and Data Science Strategy – Emerging Data and Capabilities

Description

JOB TITLE: Senior Manager, Risk Appetite and Analytics

LOCATIONS: Edinburgh / Birmingham / Leeds / London

HOURS: Full-Time

WORKING PATTERN: Our work style is hybrid, which involves spending at least two days per week, or 40% of our time, at one of our office sites

About This Opportunity

Economic Crime poses a threat to the safety and security of the Group, our customers, and our communities. We play a key part as one of the largest financial services providers in identifying and preventing Economic Crime (EC).
 

Against a backdrop of a changing threat environment, we must evolve our prevention, detection, and response to ensure that we're responding to the risks of today and the evolution of the threat of tomorrow.
 

We're the Economic Crime Prevention (ECP) team with responsibility for managing EC risk (fraud, money laundering, bribery, sanctions) across our business banking, commercial, and corporate businesses.
 

Between them they have more than 1 million clients from sole traders through to global corporate firms. We've an important part to play help our business achieve their growth aspirations in a safe and sustainable way. So, join us and be part of Helping Britain Prosper to advance our control framework and capabilities.

As a Senior Manager, Risk Appetite and Analytics, you'll use your extensive data analytics expertise to enhance our understanding of client transactional behaviour, inform segmentation and rules within our transaction monitoring systems, and explore opportunities to improve analysis effectiveness through machine learning.

You'll drive improvement in the use of analytics to understand the EC Risk Framework, using data from a range of sources to create actionable, accurate and timely information. Some of this data needs to be developed. You'll support longer term initiatives to redefine our approach to managing risk, replacing manual processes with automated and semi-automated code.

Key Responsibilities:

Lead the existing team to develop a robust data modelling capability, guiding customer segmentation and transaction monitoring rules within the Group Transaction Monitoring System, MOSAIC.

Build a robust process for interacting with shared service provides including FCCT and Group Data Office.

Provide analytical content to drive decision making across BCB/CIB Economic Crime Prevention.

Develop a team of analysts to support the transformation journey.

What You'll Need

Proven experience in data analytics, particularly within Economic Crime Prevention.

Strong leadership skills with a track record of managing and developing high-performing teams.

Expertise in data modelling and machine learning.

Excellent communication and partner management skills.

Excellent understanding of RCSA, Workday, JIRA and Confluence as data sources.

About Working For Us

Our focus is to ensure we're inclusive every day, building an organisation that reflects modern society and celebrates diversity in all its forms. We want our people to feel that they belong and can be their best, regardless of background, identity or culture. If you’d like reasonable adjustments to be made to our recruitment processes, just let us know.
 

If you’re excited by the thought of becoming part of our team, get in touch. We’d love to hear from you.

At Lloyds Banking Group, we're driven by a clear purpose; to help Britain prosper. Across the Group, our colleagues are focused on making a difference to customers, businesses and communities. With us you'll have a key role to play in shaping the financial services of the future, whilst the scale and reach of our Group means you'll have many opportunities to learn, grow and develop.

We keep your data safe. So, we'll only ever ask you to provide confidential or sensitive information once you have formally been invited along to an interview or accepted a verbal offer to join us which is when we run our background checks. We'll always explain what we need and why, with any request coming from a trusted Lloyds Banking Group person. 

We're focused on creating a values-led culture and are committed to building a workforce which reflects the diversity of the customers and communities we serve. Together we’re building a truly inclusive workplace where all of our colleagues have the opportunity to make a real difference.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.