Assistant Manager - Research & Analytics Insights

KPMG UK
Leeds
11 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst Senior Consultant, Assistant Manager, Manager - Belfast

Local Gov't Housing Data Analyst Temp: West London

Data Analyst Training Course (Excel, SQL & Power BI)

Trainee Data Analyst - Training Course

Trainee Data Analyst - Training Course

Data Analyst

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.