Success is Beyond the Data

I am not your typical Data person.

I don’t have an advanced degree, much less an undergraduate in an adjacent field. I also have not focused on any specific area of the data field. What I do have is over 15 years of experience working in the Data space, in the “before time” of Data Science, and have risen to an executive level that I thought I would not achieve by this age. I’ve had a successful career in retail and entertainment with a developing career in insurance tech. I’ve operated in on-prem, cloud, and hybrid technology environments while seeing Python and R come to prominence in corporate data roles. With this breadth of experience, You don’t negotiate a winding career without learning a few things or navigating some hard lessons. I’d like to share what I’ve learned along the way, sometimes the hard way, so you don’t have to.

Before we get there I’d like to share a bit of myself to ideally provide some credence to what I have to say, help you understand a bit about me, and (hopefully) validate that a meandering career and an atypical educational background is not just ok, but a strength.

For example, I’ve been able to successfully push business stakeholders by relating a current problem to another problem that I’ve seen and solved in another industry. Being able to think differently than your stakeholders or coworkers is invaluable as you bring a different, contrasting, perspective which only yields better solutions.

I don’t want to give away what I want to write about until the end, so hang on. :)

My undergraduate isn’t data-adjacent (Product Design). While I have started a couple of Master’s degrees in Data Science and Survey Research, I haven’t completed them due to lost interest or life taking me in a different direction. Much of what I have learned and delivered has been self-taught through the help of several great friends and mentors, as well as countless hours outside of work reading and learning.

My wandering through various roles has led to an atypical career which has rewarded me with a broad perspective on the field and a range of experiences to pull from. Early in my career, I cut my teeth on writing finance and compliance report queries before moving into CRM Analytics where I supported Direct Mail and Email marketing campaigns. At this point, I was unsure of what I wanted to do, so I wandered into an opportunity in Data Operations where I brought Hadoop into a Fortune 50 company when it was still relatively new (I do not want to relive my Hadoop 1 days). From there I was recruited by a peer to build out recommendation capabilities on our e-commerce platform, which developed into me leading and building the Data Science team there. This is where I learned that I loved building teams. Building teams and aligning them organizationally is just another problem to solve with data. Data in this instance is what you know about the stakeholders and their personalities, the problem needing to be solved, and aligning the right resources to solve the problem.

After a few years in the e-commerce organization and building a robust team, I decided that I didn’t have enough experience in business-facing roles, so I joined a very large media company run by a mouse. I spent nearly four and a half years there building a team from 2 to nearly 40 and spreading my team from supporting marketing for one organization to supporting a wide range of functions across many organizations. As you might expect with such an increase in responsibility, this time wasn’t without its challenges. The pace of the team build was aggressive, we survived a multitude of reorganizations and layoffs, and we were the data science team in a sea of media researchers that were trying to get people to break their 50+ year reliance on Nielsen data. These obstacles were overcome, but draining and frustrating. There aren’t many jobs where you don’t retain a few scars from hard lessons learned, and this job was one of those.

Once the journey with the mouse was complete, I joined my first startup: if you can call a 9-year-old, 800-person company a startup. Over the past 3 years, I’ve moved from running Product Science to being the Head of Data Science and Data Engineering while managing all of that through an acquisition. This is a story still being written — ripe with opportunity. This is the first company I’ve been in that has been willing to invest in data solutions as a marketable and revenue-generating capability.

While I have had a meandering career, and what I have learned has helped me be successful, I attribute my success in the field to 3 things, and none of them are directly related to the quantitative methods that I have learned or my ability to wrangle data.

First and foremost are the relationships I’ve built and the luck of being in the right place at the right time.

Secondly, putting myself out there and am always willing to do what needs to be done even if it’s outside of my comfort zone.

Last, but not least is my tenacity in solving problems.

Much of data work involves delivering solutions to ambiguous problems that are hard to solve. I’ll not dig in too much here as I look forward to unpacking each item in detail over the coming months.

This blog will be a bit different than what you are used to seeing in the data space. For instance, I will rarely pontificate about the merits of any algorithm or new technology. There are plenty of great content creators out there, and given you are reading this, you are likely to know of a good source or two of your own. I have no interest in adding my voice to that choir.

What I want to share with you is what I learned beyond the data. Yes, you need to understand the fundamentals of statistics, machine learning, and AI. Yes, you need to keep current with the rapid evolution of the field. However, you rarely see content related to being successful in the Data field beyond the algorithms and technologies.

I want to give back to you and the field something that lasts and can reliably increase your success as a Data Scientist or Data Engineer. As a result, this blog will focus on 4 core themes:

Problem Solving, Stakeholders, Impact, and Development.

My own goal and promise to you is to release a new blog every two weeks. I am ironing out a list of topics for the next year and structuring how I’ll release these topics.

See you in a couple of weeks. Thanks for reading.