I have 'the best job in America' - here's what it's like

"I grew up in Connecticut and went to Vassar College for my undergraduate degree. I worked in New York City, and then I attended business school at the University of Connecticut.

"I realized during my undergraduate years that I wanted to study business, but Vassar was a liberal arts school and there was no business major. I majored in economics and discovered that I had a real passion for the psychology behind marketing. I wanted to know what drove people to make choices as consumers.

"I worked in New York City during 9/11 and I watched it all happen. It was a real turning point for me because I decided I wanted to leave the city and go back to where I grew up, Connecticut.

"I got my MBA in Marketing Intelligence at the University of Connecticut. I chose this track because I was interested in the combination of behavioral data and statistical tools to draw analysis. I wanted to know what drove people to make choices."

"I worked in insurance right out of business school, and it was great exposure to what business marketing was like. It was all about education and reach. How can we get our voice out to more people? How can we educate them on the importance of saving for retirement?

"My first true data crunching job started in 2006 at a small database marketing firm, really a two-man shop. I loved the work I was doing, but there wasn't much room for growth. I knew I needed to move on in order to work with the big names in business. That's how I ended up at Toluna.

"On another level, I think there is something in my personality that drew me to this field. I'm a pretty skeptical guy. I find it difficult to believe something unless I can see the proof, and for me, the proof is in the numbers."

"When I got into this field in the mid 2000s, agencies and firms didn't really know what they were looking for. They knew there was a demand for data analytics, but there wasn't a big demand for computer science majors or math experts.

"When I applied for my current job, I got it because I was a candidate that could demonstrate experience working with data and crunching numbers, but more importantly I could tell a story about that data. And that's what I look for in any potential new member of my team. I want someone who can think quickly on their feet, someone who can talk to a client and frame their findings effectively. I want someone who isn't afraid to make a decision and stick by it.

"This job takes a lot of independence, and if you can't take ownership of your ideas it's not going to work. You have to be able to present information clearly and concisely. The job isn't just about crunching numbers and making graphs. It's about finding meaningful patterns to gain insights for your clients; a big part of the job is presenting your findings effectively."

"The salary for this job is certainly competitive. People have a lot of educational background and advanced degrees. PhDs and MBAs are fairly common in the industry and this expertise comes at a premium for employers.

"There is also demand to consider. Companies are increasingly turning to data analytics to find profitable avenues for their businesses. As these needs increase so does demand for people with expertise in statistical research. As a seasoned data scientist you are going to be getting calls from recruiters regularly, which tends to drive salaries up."

According to Glassdoor, the median base pay for data scientists in 2016 is $116,840.

"I wake up at 6:30, usually because my 3-year-old son has climbed into bed with me. I'm in the office by 9:00 and my first task to sort through my emails. We are a global company so we get emails 24/7 from clients and colleagues all over the world.

"First, I see if I have any urgent asks from clients. Are there any pressing problems that need to be addressed? This happens pretty regularly, as client relations is a major part of what I do. I am in a management position so I can delegate some tasks, but I also like to roll up my sleeves and get my hands dirty like everyone else on my team.

"Throughout the day there are several typical tasks: writing research reports, forming questionnaires, and conducting specific statistical analyses like segmentation, regression analysis, MaxDiff analysis, TURF analyses, and choice-based conjoint studies, and price laddering studies, typically using the Van Westendorp price sensitivity model. These more specific statistical requests are fairly new in the past few years. As clients have learned more about how much they can get out of their data, we have adapted to deliver the best results. It's why we try to bring everything we need in-house, like state-of-the-art technology and our robust consumer survey panel.

"There is no typical day. That's why I like the job so much — there are always new challenges. But an example of some of the troubleshooting we might do is when we get stuck in the field doing client research. This basically means the population parameters that the client wants to investigate might be too narrow, and they are preventing us from finding meaningful results.

"Getting stuck in a field is a pretty common problem and our task is to find ways to alter our approach without compromising the data and the findings. A client may want to limit their investigation to left-handed surfers in Australia but we might have to make alternative recommendations in order to get results. Having our own survey panel with a large community of respondents is really essential in these cases, but they can still be challenging to address.

"I leave at around 5:30 and plug back in from 8:00 to 10:00. I usually work 10 to 11 hours a day. I try to avoid work on weekends when I can, but you never know when something urgent might come up."

"I don't sit in a dark cubicle all day. I am not in love with my calculator. This job is analytical and intuitive.

"I think people misunderstand this job because they think it's all about the math. Really it's about problem-solving. Clients bring us questions and we use state-of-the-art technology, statistics, and data to bring them the insights they need to make informed decisions. We are really on the frontline of marketing, helping top-level executives make consequential decisions about the future of their business and their products."

"The best part of the job is definitely the variety. I love coming into the office not knowing what's going to come up, what client challenge I can solve. It's not for everyone, I know, but I really like that aspect. And we do it well here, we have a pretty small team working on research, but it helps us stay nimble for our clients.

"I really love that the job asks you to think outside the box every day. Clients are always bringing new and interesting asks to us, and I love finding a creative solution. You might think that when a client knows exactly what they want and how they want it, my job would be easier. The reality is when a client comes in with only a general idea, my eyes light up. We have great technology here, which means we can get really creative with how we answer client questions. I love that."

"Even though working with clients is one of the best parts of the job, it can also pose its own challenges. Tight deadlines and unrealistic expectations can make our lives difficult. But it's all about how you face the challenges. If you have the right tools and the right team, like I do, you can tackle it."

"I would say I was pleasantly surprised when I found out data scientist was the number one job in America. I didn't realize so many people knew about data science. We operate largely behind the scenes from a consumer perspective, so this kind of recognition is really great.

"I would certainly encourage people to pursue this field. It is stimulating work, and every day presents new and exciting challenges. I started working in this field in 2006 and I don't find myself wanting to do anything else.

"It's a fast-growing field, so there is also the matter of job security. The amount of data that needs to be analyzed is only going to grow, and with that will come demand for more capable people to search for meaningful patterns. I definitely think it's something people interested in research and marketing should look into."