Data Scientist - McKinsey Analytics

Qualifications

  • MSc or PhD degree in the field of Computer Science, Machine Learning, Applied Statistics, Econometrics, Mathematics
  • 3+ years of working experience in statistical modelling and/or machine learning
  • Experience in applying data science methods to business problems
  • Programming experience in at least two of the following languages: R or Python, MATLAB, SAS, Java, Git, Spark, Scala
  • Ability to explain complex analytical concepts to people from other fields
  • Strong presentation and communication skills
  • Business level fluency in English and Swedish

Who You'll Work With

You'll work in Stockholm as part of the McKinsey Analytics team. McKinsey Analytics works with clients to build analytics-driven organizations. We combine the latest techniques with deep industry, functional, and analytics expertise to help clients capture the most value from data.

You'll join a global team of more than 1000 experts in machine learning, big data architecture and AI. We help governments, businesses and NGOs actually make change happen through partnering with their top data scientists and business leaders to solve the most pressing issues. On a daily basis, you will work in an agile cross-functional team of consultants, data scientists, data architects and leaders from our clients.

What You'll Do

You will apply data science methods to improve and optimize our clients performance needs, capture meaningful insights from data and turn them into competitive advantages.

You will drive the creation of statistical models to solve specific operational problems. These problems may include: How can we predict equipment failure to do proactive maintenance for wind turbines? How can we use machine learning to predict consumer behavior? In solving these problems, you will have access to proprietary feature engineering AI and teams of world-leading experts in the domain you are working on.

At McKinsey you will not be a small piece of a big puzzle. You will be in the room, often with the senior management, working side by side with talented data scientists from leading client organizations both on technical issues and on making the change happen.


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