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Meet the Data Scientist Behind Out & Allies’ Mentorship Algorithm

Written by

Tyler Nelson, an Associate based in our San Francisco office.

Finding the perfect mentor is often a challenge – and it’s one that Tyler Nelson was determined to help his colleagues overcome. His idea? A Tinder-like program that uses a machine learning algorithm to match mentors and mentees who are members of our Out & Allies Network.

“The project – which included measuring membership trends and recruiting pipelines to create the algorithmically enhanced mentorship program – inspired me to be entrepreneurial and confident with what I could build from scratch,” says the San Francisco-based tech investor. Here, Tyler shares why he believes mentorship is so important, how his art history background prepared him to work in finance and the best career advice he’s ever received.

What initially attracted you to BlackRock, and what are your core responsibilities?

A mentor of mine told me that BlackRock works right at the intersection of investing, technology and sustainability – a trifecta for me! I work on our tech fund as our team’s Data Scientist. I help architect our research and data platform, then ultimately use that data to make investment decisions.

How did you prepare for your interviews with BlackRock?

I practiced narrating my story: Why did I study computer engineering and art history? How did I use analytics to guide my university’s record label? Why do I love investing? Figuring out what clicked and what sounded awkward was a nice feedback loop to confirm I was making the right career decision.

When telling your own story, my advice is two-fold: Be specific and be unique. If you need help, ask a few people close to you how they’d tell your story!

What are you responsible for in your role?

As a project manager within the Technology and Operations business, I lead all merger and acquisition (M&A) activity – supporting the technology platforms, enterprise services, information security and data and artificial intelligence functions, as well as large-scale, cross-functional initiatives.

What has kept you at BlackRock for almost six years?

The opportunity for continual growth. BlackRock is a sandbox of opportunities – one day I could be practicing my Python skills, the next analyzing equity markets, and the next presenting to clients. I can always seek out intellectual stimulation, so whether it’s blockchain technology or sustainability, there’s a high chance someone at BlackRock is working on it.

What accomplishment are you most proud of?

I was quite proud when my data visualization was coined the “Nelson Plot” by one of the founders of BlackRock. I was tasked with showing how hundreds of different funds would perform in a market selloff, and instead of just box-and-whisker plots, we wanted to show the full distribution of outcomes. I got to use data in a creative way to tell a story and got my trademark on it.

Tell us about the machine learning algorithm you created for BlackRock’s Out & Allies Network to help with its mentorship and career development program.

Mentorship is so important, especially within underrepresented communities. I wanted to design a pairing process that was both effective and fun: a Tinder-like algorithm that matched people with mutual interests and mentorship goals so that the pairing would stick. We had more than 300 employees register, both LGBTQ+ individuals and allies. The algorithm found extremely accurate pairings, matching a San Francisco-based managing director who studied musicology with an analyst in Tokyo who had a passion for orchestral music.

What advice do you have for people who want to become better allies?

Focus on the impact you can make. What actions can help your mentee advance their career, feel acknowledged, or learn a skill? At its essence, allyship is a type of relationship, so as with any relationship, proactivity and consistency go a long way.

You’ve studied engineering, economics, art history and data analytics. Have any of those topics contributed to your work at BlackRock in surprising ways?

Totally! I’m a firm believer that analyzing art is very similar to choosing stocks. In art history, you analyze a painting, contextualize it in its time period, then tell the story of its impact. Same with a stock: You understand its fundamentals, compare its valuation and competitive position versus its peers, and then make a thoughtful recommendation.

How do you practice work-life balance? Are there any related benefits or perks that you take advantage of at BlackRock?

I’m a member of the San Francisco Museum of Modern Art and the de Young Museum, both with support from BlackRock. Visiting a new exhibit after work lets me flex both the left and right sides of my brain, which helps me feel balanced.

What’s one positive change you’ve made to your workday routine since the pandemic began?

I intentionally think about which forms of communication will help fill up my social battery. Trite texts and generic Zoom calls don’t make me feel fulfilled, but meaningful one-on-one video calls or personalized notes can help sustain social relationships in a hybrid work environment.

What’s the best career advice you’ve ever received?

The best advice was “measure your success not on time spent but on impact made.” Did I drive value? Did I save my team time? Did I think systematically so this task is automated for the future? We’re not robots; we should move away from repetitive tasks and towards value-add vision.

You’re organizing a dinner party with your biggest role models. Who’s invited and what will you talk about?

It would be an eclectic trio: the host of Survivor Jeff Probst, Pokémon creator Satoshi Tajiri and TikTok icon Noah Beck. All are phenomenal storytellers in their unique ways. In an era where yesterday’s news is quickly irrelevant, it is incredible how have they have entertained their audiences for years, if not decades, on end.

A version of this article was originally published on The Muse.

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