Careers in Switzerland

Quantum Black AI by McKinsey

Variety guaranteed. Innovation expected. Impact delivered.

Expand your horizons solving the biggest real-world challenges with complex data sets and advanced-analytics tools. Work with exceptional colleagues and clients to build analytics capabilities that break new ground, transform industries, and shape markets.

Your working environment

QuantumBlack in Zurich is a growing community of consultants who are a part of an international and European community. We offer up to 6 weeks of training per year on your personal development, both on your business as well as your analytics skills. We engage with academia in order to enable you to keep your set of skills at the state of the art. Like generalists, you will work directly on site with clients and client teams to conduct hands-on rigorous quantitative analysis as part of the overall problem solving approach. Your expertise and passion for big data and rapid problem solving will help clients gain the most value from data.

Why join us

We combine the latest techniques with deep industry, functional, and analytics expertise to help clients capture the most value from data. Examples of projects and topics of interest include churn reduction, customer and channel management, and pricing and promotion optimization; and operational improvements, like fraud prevention, talent retention, and predictive maintenance, to name just a few. Such impact has been proven in over 2,000 projects in the last two years with many of the world’s leading companies and institutions.

Your profile

We are looking for young professionals, graduates or students who wish to focus on analytics/data science topics, such as personalization of offers, forecasting or scheduling optimization. Most analytics consultants have a quantitative background (Mathematics, Physics, Statistics, Computer Science, etc.) with deep understanding of statistics/machine learning, and are fluent in two or more programming languages (e.g. R, Python, SQL, Julia, SWL, GMPL, or related). We are looking for entrepreneurial team players, ready to work in interdisciplinary teams with Generalists, Experts and Data Scientists.

Many routes to McKinsey

I am excited when I find new insights in previously unused data. And when we package it into a software app that our client can use going forward, it is so rewarding to see the solution come to life.
Andreas Ess
Partner, Digital McKinsey & QuantumBlack, Zurich

Meet Andreas

Recent Projects

Using machine learning for digital payments

Together with our digital payments experts, our analytics consultants developed a machine learning model that automatically refreshes itself to predict customer attrition for a leading payments provider. We increased the ability to correctly predict customer attrition threefold and thus helped our client to significantly enhance its customer retention efforts.

Natural language processing in banking

For a major Swiss financial institution we implemented natural language processing, a branch of artificial intelligence, to understand and process text documents in investment banking. We achieved state-of-the-art processing accuracy and identified substantial cost savings.

Advanced analytics to improve clinical trial productivity

We worked with a global pharmaceutical business to use advanced analytics to improve clinical operations, and take a machine learning approach to better monitor and manage site level quality risk. Together with the client team we developed the initial hypotheses on the drivers of performance, based on which our data scientists then developed the corresponding algorithms. We employed a combination of explanatory, predictive and optimization algorithms to provide the teams with real-time decision support, as well as the possibility to review the impact of these decisions. This resulted in an increase in clinical trial productivity of ≥10%. Get more insights here.

Promotion analytics tool for a major Swiss retailer

We built a promotion analytics tool for a retail client, that based on years of transaction data can predict whether a given promotion is likely to create value for the retailer (additional revenue, margin), instead of stock-up, or cannibalizing other products.