The Ideal Candidate for the 6sense Data Science Team

 In Data Science, Inside 6sense

Meet Chris Gutierrez, 6sense’s Chief Data Scientist. His sidekick is a rescue poodle-mix named Data who is known around the office as Little Data. Chris was born and raised in a small town called Erie, Colorado, just east of Boulder. Chris grew up skiing and snowboarding. He studied at State College of Denver and got his Masters from CU Boulder. Though he has moved around a bit to work for companies like Google, Airbnb, LinkedIn and Expedia, California is where he wants to stay.

Can you walk us through your background?

I was a data scientist before the term “data scientist” existed. I started off in environmental consulting in the late ‘90s, then worked for a couple of ad-tech companies. I worked with engineers to create a collaborative filter for a recommender system back when getting that to scale was a challenge. In 2015, there are many off-the-shelf approaches, but in 2001, it was a lot of work, but fun work.

Since then, most of what I’ve done has been about supporting products, managing data and analytics teams, developing data visualization and dashboards and working with product managers and external clients.

I worked for AdKnowledge and then Google, and then I moved to Seattle to work for Expedia. After that, I came back to San Francisco and worked for LinkedIn and Airbnb. I’ve also advised and contributed part-time to several startups. Working with great companies has allowed me to learn from some of the best in the industry.

Why did you join 6sense?

The main thing that got me excited about 6sense were the people. All the founders are great. Amanda, our CEO, is full of energy and is always positive and passionate about what she does. I trust her vision and her ability to keep us successful. The other founders are all top-notch engineers, and they have great business acumen. Each understands our customers’ needs and how those relate to the data. Then there’s Mark Dye, he brings in great strategic partners with unique and valuable data. As a data scientist, I’m only as good as the data I can work with. He makes sure we have plenty of great sources.

Another draw is that 6sense is really one big analytics engine. Airbnb and LinkedIn are great companies, and the work I did there helped to support valuable products, but at 6sense, analytics IS the product. That’s a lot of fun for a data scientist. Data science directly affects the company’s bottom line. Good or bad, we’re front and center.

What can data scientists do at 6sense that they cant do elsewhere?

Every customer has different data. Not just different records, but different features. Because of Mark Dye, we also have a lot of great third-party sources to link to each customer’s data. It’s similar to the best part of being a consultant; the work never gets boring. Unlike consulting, however, we can leverage many generalized systems so that preparing the data isn’t from scratch each time. We can scale without linearly adding data scientists.

Where do you see 6sense headed?

I see us headed up, way up. Because analytics is at the core, I see a lot of innovation happening at 6sense. We’re constantly trying new things. I just started, and we’re already testing three approaches to analytic platforms. We’re working to make things scale and be dynamic, because we have a combination of not just number of records, but also adding and testing new features. We have to build our models to be flexible with new data and not just size. In short, I see a lot of work – a lot of fun work – and potential.

Who’s the ideal candidate for the 6sense data science team?

We’re looking for people with flexibility and mental agility. Someone might be a great modeler, but is one-dimensional and works best in large companies as the supporting cast. At 6sense, we’re looking for people who are well-rounded. They need to have good business sense.

They need to look at a product and know what questions to ask. They need to know how the product is going to be used and make sure their model works for how it’s going to be used. Ideally, they can work directly with customers to get first-hand knowledge of what they want to do, discover what they need and find out exactly how they use what we give them.

The technical makeup can be very different. We could use a solid engineer with a little background in modeling or we could use a light engineer, someone who can at least move data around, but is really a strong modeler. We work as a team so we can balance things out.

Whats something interesting about yourself? 

One of the things I’m proud of is a Dale Carnegie class I took over ten years ago. I got a Highest Achievement Award from my class. The award isn’t the big thing, but what I got out of the class is important to me. I learned so much about building and maintaining relationships that it’s more valuable to me than my master’s degree. It’s not so much tricks and techniques, but how to think about things. It made a big difference for me at work and home.

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If you’re passionate about using data at scale to solve a challenging problem, talk to us. We’re hiring!

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