Reflections of a New Manager

One year in as a data science leader and first time official manager

About a year ago, I interviewed for a fairly important sounding role. Since this was an internal position, I did my due diligence and solicited advice from my network of people-in-the-know. Some gave me helpful guidance, some gave me honest feedback on why they didn’t think it was a good role, and one told me that I’ll likely get the job because I check three diversity boxes.

Fast forward two months, I was offered the position. When I told the people I asked advice from, they reacted mostly with shock and one person suggested that it must be because I know the right people.

Learning #1: Taking on more visible roles means that I have to deal with more people having and sharing opinions about me.

So after almost 15 years of working as an individual contributor in the insurance industry, I became an official manager of a small team of data scientists in 2021. For the next several months, I did very little besides work.

I did the things that I knew had to be done before taking the role: creating a vision for what I want the team to be doing, building a good team culture, establishing best practices, liaising with business partners, managing ongoing projects and developing new projects.

And, I did the things that I hadn’t given much thought to before taking the role but needed to be done: addressing visa issues, addressing unprofessional behaviors, hiring to refill headcount from resignations, hiring and being ghosted by interns (it’s a tough job market), squabbling with HR on unreasonable salary offers, pushing back on a merit raise structure that I felt was unfair, dealing with employee concerns about returning to the office, learning IT systems and security considerations, learning cloud technologies and modern app development tools, politicking to obtain necessary approvals, and performing a lot of manual data cleaning work.

Learning #2: For technical managers, HR and IT issues will take up a good chunk of time. Make friends where you can and choose your battles.

In hindsight, perhaps my view of what this role entailed was too naïve. I did expect that some things would come up with HR and IT that I would need to deal with. I didn’t expect the extent of the dealings, nor did I expect how emotional I would get. Mostly, my emotions registered as feeling angry, which I then needed to try to present externally as just being serious because angry women lose influence. But to be honest, when I’m notified that I have to restart a 10-step approval process because someone added an extra whitespace at the end of an IT-managed identity name… I imagine flipping my table (╯°□°)╯︵ ┻━┻.

Learning #3: For any manager, state of mind and emotions are much more consequential. Effort should be made to get them under control.

There were a lot of things that I needed to learn quickly in the new role. And I needed to be able to apply those learnings fast. Since I was trying to lay the groundwork for my team, I felt that any misstep could have big undesirable consequences.

I also needed to keep up with insurance business news so that I could network effectively with our business partners and get their buy-in for our projects. In my department, from a data and analytics perspective, we are in the unfortunate situation of not being able to focus on any one specific domain and have to be interested in every major line of business.

On top of the things I felt that I had to do, other analytics professionals would send me information about new educational content and techniques in the open source or insurance community. Every day, I also receive a list of recommended articles from Medium that looks something like this:

• <LARGE NUMBER> Techniques all Data Scientists Should Know
• <LARGE NUMBER> Killer Automation Scripts for Your Projects
• <LARGE NUMBER> Ultimate Data Visualization Tools
• <LARGE NUMBER> Python Operations for Your Data Analysis
• <LARGE NUMBER> Features Your ML App Can’t Do Without
• <LARGE NUMBER> Tools You Need to Add to Your Workflow
• <LARGE NUMBER> Fantastic Packages
• Working with <PYTHON LIBRARY THAT SOUNDS LIKE GIBBERISH>
• Working with <ANOTHER RIDICULOUSLY NAMED LIBRARY>

Enter imposter syndrome.

This isn’t new for me, but my feelings of inadequacy were more addressable when I was in junior roles. All I had to do was to work more hours, and since my field was so specialized, the extra hours were manageable. After moving into a management role, I had to conclude that there are not enough hours in the day for anyone to stay on top of the emerging trends in data science.

Learning #4: Realize that having things to learn is an expected and good thing. Managers get to talk to a lot of people who each specialize in some area, but no one person can know everything.

Now that I’m almost one year into the new job, I find myself still working much more than is probably healthy. Every day, more items get added to my to-do list than get checked off. And every day, I discover more things that I wish I had time to learn about. Prioritization might be the most important skill that I am developing.

I wonder what the next year will bring?