Saving lives as a data scientist

Josh loved traveling, problem solving, and doing things that matter as a data scientist; and found a spectacular way to blend those together at a boutique consultancy. After stints in academia and industry, he enjoyed having a myriad of projects and lots of variety.

It was then that a McKinsey tech recruiter contacted Josh, and soon after, he found himself at McKinsey. Josh describes how McKinsey allowed him to, “work on hard problems that actually matter,” as Josh describes, and stumble onto a passion for healthcare.

After a few years at McKinsey and CVS Health, Josh is now a Facebook healthcare-analytics lead. He shares with us in these clips the meaningful work, diverse tech-focused teams, and knowledge he gained at McKinsey that helped him grow as an analytics leader.

Data science work that matters

For data scientists who want challenging work with impact, Josh says McKinsey is the perfect organization. In this video, Josh shares how McKinsey offered him the chance to travel to patients’ homes to help him better understand how his advanced-analytics work can better patients’ lives. Josh described the experience as “only at McKinsey.”

He also speaks to one of his most rewarding experiences, where he used journey-analytics modeling to help save lives: ensuring patients facing a rare and previously incurable neurological disease could get a new, life-saving drug.

“All of the projects McKinsey works on matter. Only at McKinsey do you have the opportunity to work on things like this over and over again, in different industries, across different dynamics,” says Josh. “If meaning is at the top of your list, I doubt there’s a better place to be than McKinsey.”

Diverse, multi-disciplinary teams

“The type of team we work on is always diverse,” says Josh. Not only do clients then get the best in every dimension; but as a McKinsey colleague, it allowed him to work alongside colleagues with other strengths, supporting one another’s growth and learning. Josh shares how alongside McKinsey consultants and tech practitioners, our teams come together with complementary skills to solve some of the toughest problems as one client team.

From classic McKinsey projects to design-thinking, advanced-analytics and engineering-led client challenges, McKinsey teams come together at the start of a client project to define the core characteristics of the challenge, and then bring together the optimal blend of experts to solve it.

In addition to broad exploration in data science in this case, McKinsey offers technologists the opportunity to specialize, if they’d like. For instance, Josh supported data science on a marketing & sales, journey-analytics team, which focused on event sequences and deep learning to better predict and prescribe actions to enhance the user experience for customers, patients, and employees.

From mobile apps to marketing strategies

Data scientists like Josh use many tools including one of his favorites: McKinsey’s proprietary journey-mapping platform, Argon-X, which has tracked 350+ million journeys, and 5.3 billion user touchpoints to date. Those stem from 15 customer, product, digital, traditional, and unstructured data sources—including Personally Identifiable Information (PII) and Health Insurance Portability & Accountability Act (HIPAA) related data—allowing colleagues to build actionable algorithms that break down touchpoints in a patient journey, for instance.

As Josh shares in the video below, depending on the client project’s scope, they collaborate with McKinsey software/data engineers, user experience (UX) designers, agile coaches, marketers, generalist consultants, project (engagement) managers, and fellow data scientists. Together, they work with the client to transform that algorithm and UX through the strategy, insight, design and/or implementation phases—helping deliver a life-saving drug to patients at a global scale.

“Sometimes, all we need for a client project are analytics professionals like data scientists, data engineers, and analytics translators, because the problem is purely analytical. Sometimes, we need the power of analytics people collaborating with designers to build a mobile app, or the analytics teams join with traditional consultants to create a product marketing strategy,” says Josh.

Whatever the end goal, our firm of 30,000+ colleagues—and a tech community of more than 4,500— makes for a powerful team to support client work on nearly any problem you can imagine.

Three weeks annually of training

Hailing from a ~50-person consultancy prior to McKinsey, Josh confesses some initial apprehension about transitioning to a 30,000-person firm like McKinsey. But those feelings quickly evaporated when he saw the support he would receive here. In the video below, he shares his onboarding experience, and access to at least three weeks annually of data-science and leadership training to help him be at his best as an advanced analytics leader.

“Having worked for at least six different companies, I can confidently say McKinsey is the absolute best when it comes to training, support, mentorship, and onboarding. I actually wanted to try some not advanced-analytics things here at McKinsey, and I was provided that opportunity. All I had to do was raise my hand and say, ‘Hey, I want to do this other type of project’ … and they said, ‘Go for it.’”

Find a job like Josh’s

About Josh

Based in New York City, Josh is a McKinsey alum, and healthcare analytics and strategy leader at Facebook. Before joining Facebook, he was vice president of customer analytics at CVS Health. While at McKinsey, Josh was a data scientist and senior manager, as part of the firm’s marketing & sales and digital teams.

Josh also has worked as a data scientist at boutique consultancy and at IBM; a predictive-modeling graduate lecturer at Northwestern University; a co-founder and chief financial officer of a biotech startup; and a financial analyst at Boeing. He holds a bachelor’s in finance, chemistry, and business administration from Carnegie Mellon University; and a master’s in predictive analytics from Northwestern University.

For more information on McKinsey's data science career paths, visit

Note: All videos were filmed prior to the COVID-19 pandemic.

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