Associate Intern

McKinsey & Company
London
11 months ago
Applications closed

Related Jobs

View all jobs

Associate Data Engineer - Belfast

Pre-Sales Engineer / Product Associate

SC Cleared Azure Data Architect/DBA (Azure SQL, Cloud)

HR Data Analyst

Senior Data Engineer (Consultant)

Data Engineer

You will join one of our offices around the world for 8-10 weeks, usually in the summer, to work in teams and directly with our clients.
In this role, you will help our clients in private, public, and social sectors solve their most pressing problems. You will also work with many experts, from data scientists and researchers to software and app designers.

You'll work in teams of typically 3 - 5 consultants to identify, and oftentimes implement, potential solutions for a specific client problem or challenge. Together, you will help clients make lasting improvements to their performance and realize their most important goals.

Over the course of each project, you will gather and analyze information, formulate and test hypotheses, and develop and communicate recommendations. You'll also present results to client management and implement recommendations in collaboration with client team members. In some cases, you will be asked to travel to your client site.

When you join McKinsey, you are joining a firm whose culture is distinctive and inclusive. We will accelerate your development as a leader to create positive, enduring change in the world. As an associate intern, you will receive training and coaching on how to better:

  • Structure ambiguous problems and take action to solve them
  • Synthesize clear takeaways from complex information into clear takeaways and recommendations using both qualitative and quantitative methods
  • Work effectively with diverse teams to come up with the best solution and move people and organizations to act
  • Establish trust-based relationships with clients to better serve their organizations 
  • Communicate effectively with all audiences, including senior leaders, in a structured manner
  • Develop your leadership style, leveraging your own passions, strengths, and personal values

McKinsey believes in strengths-based development and coaching, and you’ll receive frequent mentoring from colleagues. This will include a senior colleague from your office or practice who will help you grow and achieve your career goals. Additionally, you will have a professional development manager who manages staffing to help you choose projects based on your priorities as well as the needs of client service teams.

While all consultants develop specialized knowledge as they progress with McKinsey, most are initially broad in their focus, meaning they do not need specific industry or functional expertise to be successful. For consultants who join McKinsey as experienced professionals, this can mean building on previous knowledge or developing experience in an area that is completely new.  

  • Bachelor’s degree; Advanced graduate degree in progress (e.g., MBA, PhD, etc.); Academic degree requirements may vary by country
  • Ability to work collaboratively in a team and create an inclusive environment with people at all levels of an organization
  • Capability to drive an independent workstream in the context of a broader team project
  • Comfort with ambiguous, ever-changing situations
  • Ability to break down and solve problems through quantitative thinking and analysis 
  • Ability to communicate effectively, both verbally and in writing, in English and local office language(s)

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.

Quantum-Enhanced Machine Learning—Propelling AI into the Next Frontier

Machine learning (ML) has revolutionised how we interpret data, build predictive models, and create intelligent applications. From recommendation engines and self-driving cars to advanced genomics and natural language processing, ML solutions are integral to nearly every corner of modern life. However, as data complexity and model size continue to skyrocket, the computational demands placed on ML systems grow in tandem—often pushing even high-performance classical computers to their limits. In recent years, quantum computing has emerged as a tantalising solution to these challenges. Unlike traditional digital systems, quantum computers exploit quantum mechanics—superposition and entanglement—to process information in ways that defy conventional logic. As these machines mature, they promise exponential speed-ups for certain tasks, potentially reshaping how we approach AI and data-intensive challenges. What does this mean for machine learning? Enter quantum-enhanced ML, a new frontier where quantum processors and classical ML frameworks unite to accelerate model training, tackle high-dimensional data, and solve complex optimisation tasks more efficiently. In this article, we will: Unpack the current state of machine learning, highlighting key bottlenecks. Provide a concise overview of quantum computing—why it’s radical and how it differs from classical technology. Examine potential breakthroughs in quantum-enhanced ML, including real-world use cases and technical approaches. Explore the roles and skill sets that will define this quantum-AI era, with guidance on how to prepare. Discuss the roadblocks (like hardware maturity and ethical concerns) and how they might be addressed in the years to come. If you’re a machine learning engineer, data scientist, or simply an AI enthusiast fascinated by the next wave of computational innovation, read on—quantum computing could become an integral part of your future toolkit, opening up job opportunities and reimagining what ML can achieve.

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!