How I Got There: McKinsey & Company Senior Data Science Analyst | Robert Alward, MSB Alumni

Robert Alward, Senior Data Science Analyst & MSB Alumni

Posted in Student & Alumni Stories

Robert Alward graduated from Georgetown University’s McDonough School of Business (MSB) with a degree in Operations and Information Management (OPIM). During this interview, Robert shares about his experiences that led him to his current position as a Senior Data Science Report Analyst at McKinsey & Company. Learn how Georgetown shaped his path, how he got to his current position, and more insights about breaking into the consulting industry.

What activities did you participate in while attending GU that you found the most valuable and why (clubs, research, internships, volunteer, etc.)?

Clubs: Georgetown Ventures, Innovo, GUThai, – These clubs gave me an awesome peak into worlds that I was excited about including VC, Consulting, and Thailand. They gave me a low-stakes way to practice talking to people, seeing how I could provide value, and growing my presenting skills.


  • DevGlobal, is a small consulting firm where I was able to join and get hands-on experience delivering to real clients who were paying us. Got great mentorship from more experienced leaders and saw how to sell, present, and talk to clients about exciting new developments.
  • Akamai, is a large but unsexy technology company working in the cybersecurity space. It was awesome to be surrounded by people who were deep into a technology space and I was given a lot of freedom to explore and try new things while building my Python and Machine Learning skills.
  • NASA Develop is a program for college students and recent graduates to work on meaningful projects using NASA’s data and connection to help local governments and non-profits using state-of-the-art Data Science techniques.

Research: Student Undergraduate Research Fellowship — I worked with an awesome professor Elizabeth Ferris, who I was able to learn a ton from and saw how data science was necessary for every industry and technique.

How did you find your current position?

From my first week at Georgetown, I was introduced to the world of consulting, which fascinated me with its strategic problem-solving and impact on businesses. I wanted to learn more so I attempted to join consulting clubs (which eventually worked even though Hilltop, HMFI, Innovo, and others all rejected me on my first application). I then delved into consulting-related work, absorbing knowledge about various frameworks and methodologies used in the industry. This academic foundation provided me with a solid understanding of consulting principles and sparked a keen interest in pursuing a career in this dynamic field.

Outside the classroom, I actively participated in the entrepreneurship department and sought roles that allowed me to practice what I had learned. These platforms like my internship and work at DevGlobal offered valuable hands-on experience, enabling me to apply theoretical knowledge to real-world scenarios, work on case studies, and improve my analytical and presentation skills. This practical experience was instrumental in honing my consulting capabilities, preparing me for the rigorous demands of the industry.

Despite my efforts working on casing and my interest in consulting, I faced a setback when I didn’t secure an internship with McKinsey or any other prestigious consulting firm. I then was forced to shifted my focus to data science, recognizing its growing significance in strategic decision-making. I deepened my knowledge in this area through a statistics minor and self-taught coding skills, eventually landing a data science internship. This pivot not only broadened my skill set but also opened new doors. When I re-applied to McKinsey, this time for a data science role, my diverse background and persistence paid off. I received an offer, marking a significant milestone in my career journey and a testament to the power of resilience and adaptability.

“I was surprised by how much ownership at the start of my time at McKinsey. Within my first 2 months, I was the only data scientist on a project leading the modeling and analysis work. I continued to be given a ton of responsibility and grow in Software Engineering Skills, Data Modeling Work, and Consulting and Presentation Skills.

What does a typical day or week look like and/or can you briefly explain tasks involved in your work?

Typical Day:

  • Look through my To-Do list and prioritize what I have to do
  • Meet with my team to prioritize and get review on the prior day work
  • Work through the data science tasks
  • Have meetings with clients to understand questions
  • Have meetings with clients to present my work
  • Have meetings with partners to understand how to get better and present to clients

Typical Week

  • Start the week planning for the future of the project and the week
  • Travel to a client site or co-location site
  • Work with the team on presentations and planning
  • Do the data science modeling work required for the week
  • Present to the client at the end of the week
  • Meet back up with friends at happy hour on Friday

What surprised you the most when you started working?

I was surprised by how much ownership at the start of my time at McKinsey. Within my first 2 months, I was the only data scientist on a project leading the modeling and analysis work. I continued to be given a ton of responsibility and grow in Software Engineering Skills, Data Modeling Work, and Consulting and Presentation Skills.

What skills are most needed in the industry and/or job you work?

Technical Skills:

  • Data understanding
  • Some coding skill
  • Ability to make complex problems into clear roadmaps

Non-Technical Skills:

  • Good at talking to people
  • Ability to clearly present
  • Ability to understand a problem and address the key questions people have

What are the best ways for students to learn more about your industry and/or stay abreast of trends in your industry?

The three best ways are through newsletters, doing the work, and keeping up with what is happening in the world.

1) Newsletters: Data Science Weekly, The Generalist, Not Boring, SITALWeek, AI Valley

2) Work: Find a small company that you can help for free or cheap, work with clubs, show you are smart and dedicated and people will want to help you.

3) Mentors and Connection: Develop mentors in the space either from School, other connections, or cold outreach. Keep in touch and hear what people are doing on a day to day.

If you could go back and change one thing, what would that be?

I would get started on real-world projects earlier. Work for free as early as possible to develop real-world examples. Make a portfolio earlier and learn from people around you.

Connect with Robert on LinkedIn.

Interested in hearing more stories? Check out the rest of our How I Got There series.