It takes more than analytics

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 was the best technical work you did in the last year?

One of my last projects was for a major airline company. We created a flight destination recommendation system. At the same time, we migrated data to the cloud, developed a model, and ran a marketing campaign. It was very challenging and interesting to see how analytics, business and IT implementation came together to make change at a top company.


How does your work compare to this datathon?

On a day–to–day basis, I work on creating machine learning models that can best be translated into business insights. This datathon is special because it allows participants to put themselves in a McKinsey data scientist’s shoes. We want them to generate a very good analytical solution and develop actionable recommendations and communicate them to key stakeholders. If you participate, remember to ask yourself what would you recommend to a client based on your findings?

How would you advise participants to prepare for the challenge?

Before the competition, work on an end–to–end machine learning project, focusing on communicating your results. On the day, my advice would be to be relaxed and enjoy it. Being in a competition is very motivating, but there is much more to experience during the datathon. Participants will get first–hand knowledge of data science at McKinsey and, network with firm colleagues and other participants.

Find a job like Natalia

About Natalia:

I am a senior data scientist at our Advanced Analytics Hub in Madrid. Before joining McKinsey, I did a PhD in applied physics and nanotechnology. During my two-and–a–half years at the firm, I have travelled around the world working in industries such as telecommunications, banking, airlines and basic materials. In my free time I relax by cycling and playing tennis. I love cats.

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