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How to get a job at McKinsey & Co: learn this programming language

Getting your foot in the door at one of the top consulting firms is no easy task. At McKinsey, for example, more than 750k people apply in given year. Fewer than 1% are accepted. That trumps the lowest acceptance rate at top investment banks like Goldman Sachs (~ 4%) by a wide margin. So how do you stand out from the crowd? Learn how to program with R and target the growing analytics teams.

Like banks and hedge funds, consulting firms are on the hunt for data engineers and data scientists who can design algorithms and build complex models. All the MBB firms (McKinsey & Co., Bain and Boston Consulting) have dedicated analytics teams that work alongside their consultants to analyze huge data sets to help drive business decisions for clients. McKinsey also has the spin-off Quantum Black, while BCG has BGC Gamma.  These firms are all hungry for junior and senior-level engineers to work in their analytics departments. And they're particularly hungry with engineers experienced in a particular language: R.

New roles within McKinseys's advanced analytics team specify Python and R  as prerequisites, as do roles for McKinsey's data operations specialists. In a recent LinkedIn post, Keith McNulty, a digital and analytics leader at McKinsey in London explained R's appeal: it's open source; it's built around packages in the tidyverse, which itself was constructed around the structure of data and the grammar of data manipulation; it has a strong community of passionate users; it has strong options for document and app publication and deployment; and it's easy to teach. 

McNulty is so passionate about R that he's written his own starter guide to R packages (a package is the name for a fundamental unit of reproducible R code) which you can access for free on Github. If you want to go deeper into R, he suggests you acquire the book 'R Packages by O'Reilly,' which you can access online here or buy from Amazon. 

Knowing R won't just get you a job at McKinsey & Co.. Data from Burning Glass suggests that banks like RBS and HSBC are also big hirers of programmers with R knowledge in the U.K., while Booz Allen, Deloitte and Amazon also compete for R expertise in the U.S..

As a rule of thumb, banks are typically more interested in candidates with Python and Java. However, if you want to get an analytics job at McKinsey or other consultancies, you probably need to focus on learning R and Python.

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Photo by Emile Perron on Unsplash

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AUTHORSarah Butcher Global Editor
  • mp
    mpazy38
    16 February 2019

    SQL and R is fading, but MBB don't consult firms that are at the cutting edge by definition (they wouldn't need them) so I guess that isn't surprising. Python, open source ML packages + learning APIs (Google Search Trends - https://goo.gl/Dkiraa) is where it's at now. Nothing the less, with auto machine learning on the way (turning it to a commodity), the main skill for both data scientist and business leaders will be learning to embed machine intelligence and alternative data into strategy, and processes. No an easy task.

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