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Make machine learning understandable

Nils, an analytics expert consultant from Hamburg, has learned the ability to glean actionable recommendations from analytic models is the key to success – as a consultant and a City Cup competitor.

McKinsey City Cup Datathon is an international competition in which you can apply your machine learning and coding skills to tackle an exciting social challenge. Join us on the 23rd of November in Madrid, Munich or Moscow.

What has been your best technical work at McKinsey?

One highlight was helping build customer segmentations for four regional telecommunication companies in Central Asia. My work was end–to–end, from gathering data to providing recommendations based on the outcomes of the model we built.

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During projects like this, I mainly look for creativity on the feature engineering side, as well as insights clients can use. Making machine learning understandable is the key.

How would you advise participants to prepare for the datathon?

Review the basics, like data manipulation, conversion, eliminating missing data, etc. Keep in mind the winning team will not only be great coders, but great translators, capable of delivering actionable insights. Stay focused and reserve time toward the end to synthesize your findings.

Find a job like Nils

More about Nils:

I am an analytics expert from McKinsey’s Hamburg office and part of the Marketing & Sales practice. I have been with the firm for four years, focusing on the technical and business sides of personalization. In my free time, I like to spend time with family and friends, travel the world, and lie on my inflatable boat on the River in my home town.