Oliver Wyman: Transportation & Advanced Industrials Practice (TAI) / Associate / UK

Overview

As an Associate in Oliver Wyman's Transportation & Advanced Industrials Practice, you break down complex client problems, plan and execute analyses, and identify core issues to craft impactful recommendations. You will work closely with clients and the project team, mentoring junior consultants to move work forward. The role blends deep industry knowledge with rigorous problem solving to deliver strategic insights across TAI sectors. This is a collaborative, fast-paced environment with opportunities to shape client outcomes and contribute to growth in our practice.

Pay / Benefits

• hybrid work arrangement
• remote work flexibility
• office-based collaboration
• diverse and inclusive culture
• professional development opportunities

Responsibilities

• Decompose complex problems into discrete elements and guide junior staff
• Plan and execute analyses, identifying core issues to inform recommendations
• Develop and deliver actionable client recommendations
• Collaborate with clients and project teams to advance projects
• Manage small teams to ensure timely delivery of work
• Provide unique insights within the chosen subject area

Key requirements

• 4–6 years of relevant experience, ideally with a top-tier strategy consulting firm or similar (e.g., investment banking, equity analysis, or Private Equity/VC) in TAI sectors
• In-depth knowledge of TAI sectors
• Excellent written and verbal communication skills in English
• Undergraduate or advanced degree from a top academic program
• Willingness to travel
• Proactive, initiative-taking attitude with a desire to learn
• Creativity and ability to generate novel solutions to client problems
• Strong analytical abilities to extract key issues from large data sets and complex challenges
• Ability to work fluidly and respectfully within a talented team

• strong communication
• initiative
• creativity
• team collaboration
• analytical problem solving
• data analysis from large data sets

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