Career Rocket Episode #9: Matt Gardner

Leader in Data Science, lifetime learner, and considers himself a “lazy overachiever.”

“You need to think ahead. You lay the path because the path isn’t there. ” - Matt

The goal for my Career Rocket series is to make an impact on people’s careers by sharing wisdom from successful folks with high integrity. You can also listen to the podcast of this post hosted in collaboration between DURMC and Empathetic Machines which dives deeper into the topics covered here.

Target audience for this episode: aspiring professionals in marketing

Today’s guest: Matt Gardner packs a ton of great career advice and shares his very interesting path to where he is today. I was really inspired by his passion to learn and always drive to evolve. It is not surprising that he has had such a successful career and I know the listeners will have a lot of notes to take! He was the first person to go to college from his family and we uncover his drive and mindset that put him on this career rocket trajectory.

Thanks for being on the show! How are you and your loved ones doing in the midst of all the craziness? 

Thanks for asking - we are all healthy and staying sane.   I realize I am extremely fortunate and my experience is one of privilege--which I recognize is not the experience of the majority of the world--right now or under more normal circumstances.

I also have the good luck of working for a company that is doing very well (Chegg was always about online augmented learning services for students, and these services are more important now than ever) that has really helped. As the world slowed down we have sped up.

I also cannot imagine how hard this would be with young kids - I am in total awe of my team, colleagues and friends who are parents of young kids right now! I feel lucky that my kids are almost adults and it is relatively easy for us to work from home. 

So we are doing good. I hope you and your listeners are doing OK.

Professional & personal background and highlights 

I was born in the UK and was the first person in my family to go to university. In the UK we specialized in 3 subjects in the equivalent of junior and senior high school. I was interested in math and physics and geography which led me to Aeronautical Engineering. I did well in that field but did not love it, so I decided I should really follow my passion for the outdoors. At the time, I was really into the outdoors and even went on some expeditions to New Zealand and Greenland.  My passion led to a pivot to Environmental Science--same math different domain. I then realized how much I loved science, math and programming which made learning really fun.

I loved the programming and information systems side of my studies. This interest led me to work towards my PhD, which was pure research based. I was trying to use artificial intelligence to predict pollution air levels and I got hooked on the potential of AI and machine learning. We were just starting to collect a huge amount of data, but did not understand it.  In other words, Data Rich but Knowledge Poor.  At the time, I thought we could get knowledge from this data using Artificial Intelligence, but I still have not seen any evidence of that really happening in the true sense.

I was doing all this just as the internet was born and I remember going to a meeting where it was “demo’d" to us for the first time. It was interesting but mainly because back then, scientists were using it to share weather data. I even hosted a CGI based weather site for the university with weather data and web cams on the roof of the building.  Little did I know this was the birth of my career in digital analytics. The site even had a visitor counter!  

Since I always wanted to make sure that my PhD had a path out of academia, I made sure that I was picking up transferable skills. After Completing my PhD, I landed a career in a start-up consulting firm in UK which became Data Science before that was really a thing.  That path led me through careers building and selling analytics products.

• Currently, Head Data Solutions at Chegg - reporting to CTO

• Head of Analytics at Chegg - reporting to CBO

• Director Experimentation, WalmartLabs

• Head of Data Labs and Economics - eBay

• Head of Experimentation Analytics - eBay

• Senior Manager Product Analytics - eBay

• Associate Director - CACI

• Consultant - startup and then acquired by CACI Inc

• Education - PhD in Atmospheric Sciences and Meteorology

• Hobbies - outdoors, windsurfing now kite surfing

• Family - 2 kids and wife all of whom enthusiastically decided to move from UK to US and work for more amazing companies.

How many people have you managed (includes direct reports and their teams) over your career? 

Probably over the course of my career I have managed around 100 folks from small teams (1-2) up to big teams of 40+. 

For each career stage, please share the most important characteristics to have in the field of marketing.

I am going to focus more on the marketing technology and analytics side of things rather than pure marketing - which I think of as the creative teams responsible for delivering campaigns. 

• Entry level: 1-3 years

  • The top characteristic: Have the courage to Clarify--you should know what you are being asked to do and why. If you don’t understand, ask before assuming. Ask questions to clarify goals, objectives, options and why. Context is king. If you do not know likely others don’t - have confidence to enquire. It helps the individual as well as the team. Hunger to understand.

    • Tip: inquire from a place of good intent. Don’t ask just to ask. Ask why you are asking questions. If you don’t ask, it is a missed opportunity forever. It is nerve wracking, but you should just go for it.

  • Some others: Be open minded, be able to pivot quickly, and be flexible. Change will happen fast and you should learn to adapt. Explain your intent. Have the confidence to take on new tasks, technologies learn. Problem solving.

• Mid-career: 4-7 years

  • The top characteristic: Desire to help others thrive. This includes looking out for new teammates, calling out ideas when the team seems to be heading in the wrong direction, learning how to ask clarifying questions rather than pushing an opinion.

  • Some others: Be accountable. Do what you say. Learn to debug problems.  Challenge the status quo and drive change.

• Mgr/Directors:

  • The top characteristic: Act like a coach and strive to build a team that does not need you!  Identify why they need you (or others on the team) and work to build skills and experience to empower them.  Match opportunities to the teams passions and strengths. You must be patient to nurture the talent you have.

  • Some others: Hypothesis led (critical thinking). If X is the issue then we would expect to see Y - do you see Y?  Structured thinking and communication - no matter how complex the topic. Be persistent. Most things take time so you have to help the team stay the course and get back on track after business events distract you into a fire drill or new project. If you don't, who will? Communication, Structured Thinking, and Scalability are crucial.

Looking back, please share what you feel have been your biggest drivers to a successful career?

First, I am pretty competitive, so I always had a drive to prove that I could compete with the best.  I was simply not happy to accept scraping through and this became easier once I found my passion.  Folks have sometimes said I am an overachiever, but I do not think that is true. While it might look like I am overachieving but really I just love what I am doing so I end up doing a good job.

I also find energy from learning and at different stages of my career I have always thought about projects in two ways--what is required and what is the learning opportunity.Ideally, I come out of a new process with one new skill. Sometimes, I get into trouble and have some late nights, but I always tried to learn and developed a very keen sense of when a new approach was not going to get us there on time and kept an escape plan in every project.

Over the years, this learning mindset has evolved and has given me a better sense of when my team is struggling and need help because I have been in their situation. I also have a sense of when my team is being overly cautious and not pushing themselves or the team forward. I can help them take more risks.

This focus of my learning has morphed over time. Initially I was focused on very hard skills. “For this project I am going to use only open source analytics tools.”  “For this project I am not going to use core R and I am going to use dplyr and ggplot”. The learning was focused on me and my technical skills.

As I progressed in my career, my focus became more about overall approaches to problems and working with my teams to experiment like let’s see what Bayesian stats can do to help us in get more out of our test results (spoiler - in most scenarios it doesn’t). I wonder if we can automate all our test reporting with a one liner that outputs a report and publishes it to the wiki (you can!).  Does an AB testing framework that drives performance assessment change organizational behaviors for the worse - and what can we do to mitigate it (it does and you can change it).

Now I am responsible for teams of managers and directors and cross functional areas. My focus has moved to learning new developmental and cognitive models to apply in different situations or conversations. Sometimes I feel like a Chief Psychologist! Since I am still learning, I am better positioned to help deliver the best outcomes for my team and colleagues. They get stronger, we get stronger, I get stronger.

If there was one thing you would like to tell someone earlier on in their career that you wish someone had told you, what would it be?

Optimize for doing more of the things you love instead of prioritizing the title or level of your position. Promotions will come if you are passionate and engaged because you are doing what you love doing. Don’t stick around doing something you don’t enjoy because promotion is around the corner. Move to the interesting opportunities before you have to move. Lateral moves are key here because they allow you to build a solid foundation of experiences.

Looking ahead, where do you think are the upcoming hot spots in careers around your discipline?

I think there are real opportunities to build and drive algorithms that can do a lot of what we currently have large teams working on and trying to optimize in marketing.  We built early versions of these machines in the early days of my career, but we struggled to allow the machines to experiment. Only recently has the mathematics of learning started to recognize that smart machines will need to be able to do things and measure the impact on the world to update their models.  With that math we should now be able to conceive and build a machine that experiments (invests more or less, changes creatives, tests different channels) and learns and so I see a few exciting opportunities. There will be hot spots around building these systems which will be super technical (think full on math, computer science type of background) and then we will need teams to look after the machines (will need to be technical and understand the systems and learn how they behave).  

I still think the first big breakthroughs in autonomous business operations will be in the space of marketing for a digital business and that will be a really and exciting place to be. Ultimately this will allow ourselves to see the real power of autonomous learning machines since the marketing space is such an ripe domain to try and apply this and we are already used to algorithms making decisions and using data in marketing.  To me it is natural to think we now let machines decide what to change and learn what works, but we just have to make sure we set them objectives which we want and get out of the way (which is always harder than anyone imagines!).  

What are the interesting challenges you anticipate will be coming up in your discipline in the coming years?

In the short term, I am excited by the move towards more event driven data architectures. I love events and what you can do with them. Streaming is one part and real time is another, but the most interesting aspect lies in the actionability of the immutable data that forms an event. In other words, data as events makes more sense than data in rows where you do not know what process is responsible for creating or changing it.  Events carry meaning and more context than a database table - “user_signed_up”, “user_profile_changed”, “checkout_success”.  As we move forward in this space a lot of opportunities that are unsolved open up in the market, cloud companies providing analytics on event streams at scale and trigger based orchestration of workflows, automated systems to listen to stream and extract intelligence from it that update profiles and segments.  

Longer term, I think there are some really interesting opportunities emerging around how to collect data in a way that balances the needs of the consumer as well as the platforms that need that data.  The balance right now is kind of arbitrary--we take data because we tell ourselves it allows us to optimize for the customer. But we don’t really have ways to do that while protecting the privacy of the consumer while also allowing us to more fairly put a price on the value of that data and reflect that in the products we offer. Data brokers, or third party systems (probably using some form of block chain technology) that are inserted between consumers devices and the companies with which they interact, feels like an inevitable next step in this space. And this will have implications for personalization and marketing optimization.  

Not only do you have a successful professional career, you seem to be genuinely grounded and happy. What does living abundantly mean to you and how have you carried it out?

I love the opportunity to learn and apply this passion to my professional and personal life. I have no regrets.

If you want to hear the in-depth dialogue of this post, check out the full conversation on the podcast !

Check out our full list of Career Rocket guests here

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