Assistant Manager - Research & Analytics Insights

KPMG UK
Leeds
9 months ago
Applications closed

Related Jobs

View all jobs

Senior AI Engineer | GenAI | Information Retrieval | ML | NLP | Hybrid London | Up to £130k

Senior AI Engineer | GenAI | Information Retrieval | ML | NLP | Hybrid London | Up to £130k

AI/MLOps Platform Engineer

AI / MLOps Platform Engineer

AI/MLOps Platform Engineer

AI/MLOps Platform Engineer

Job details

Location:Any UK, within occasional commuting distance from London, Leeds, or Edinburgh

Capability:Consulting

Experience Level:Associate/Assistant Manager

Type:Full Time

Service Line:Customer, Ops & Infr

Contract type:Permanent


The Customer & Operations advisory team in KPMG is at the heart of delivering innovative and large-scale customer-centric transformation programmes across all market and industry segments to help our clients reinvent their businesses for the digital age.

The Insight team sits within Customer & Operations and focuses on the transformation of Customer Insight functions.

Our programmes run deep inside organisations. We enable the development of innovative new products and services and help our clients transform into customer-centric, cost-efficient businesses. Successful candidates will work collaboratively with cross functional internal colleagues within the team and co-design solutions with broader KPMG teams and skills.


About the role

As an Assistant Manager within the Customer team, and specifically the Insight pod, the candidate will be responsible for:

  • Shaping, designing and delivering Voice of the Customer programmes and Decision-Led Insight Design engagements
  • Leading onshore and offshore teams to deliver high quality client engagements
  • Providing insight advisory services to clients and work closely with Engagement Leads/Managers and team members to successfully deliver project outcomes
  • Working with our Engagement Leads/Managers on the financial management of client engagements, developing client relationships and contributing to thought leadership


Your experience

  • Experience in a data, research or analytics field, in an agency, industry or consulting organisation


Your skills

  • Understanding of relevant technical research & analytics skills, including sampling, survey methodology, questionnaire design, widely used analytical methods and project management
  • Owning the delivery of workstreams within a complex programme – being an effective project manager – e.g. working to deadlines, managing multiple client requests, establishing processes to support client delivery
  • Adept at finding insights from data, telling the story in a visual, articulate and engaging way, and making tactical and strategic recommendations
  • Familiarity with VOC implementation and ongoing management using technology platforms such as Medallia, Qualtrics, PowerBI
  • Organisational prowess and an ability to manage multiple projects
  • Ability to demonstrate a solutions-focused approach to your work
  • Some experience of presenting to clients and/or internally


You as a person

  • Passion for research and analytics
  • Ability to build relationships with a wide range of colleagues and clients
  • Ability to learn on the job, pick up new ideas and approaches and apply them with confidence, continually reviewing working practices to ensure efficiency and improved outcomes
  • Highly organised self-starter able to work to deadlines and manage multiple priorities
  • Proactive in solving challenges – for clients, for the team
  • Interest in supporting the development of our capability, including cultural and operational improvements to the benefit of the whole team


Why Consulting at KPMG?

Technology is a critical focus for us. It underpins everything we do. We're investing in technology like never before – not least because the pace of technological change is disrupting organisations in new and challenging ways. Through advanced data analytics and emerging tech-enabled solutions like AI and machine learning, we're helping clients across diverse sectors to navigate that change. We enable them to avoid any unnecessary risks and to uncover new, transformative opportunities that could give them a competitive edge. A career here means stretching your skills and honing your expertise by solving complex problems as part of a collaborative, results-driven and supportive team. Whether we're helping our clients to reduce their costs, make better decisions, improve efficiencies or deploy the latest technologies, we bring together broad specialisms and talents to deliver robust, connected solutions.

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.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.