The demand for data scientists is rapidly growing. (In fact, we’re hiring right now.) In 2016, Glassdoor identified data scientist as the best job in America. The buzz might make you wonder what is so intriguing about the role of a data scientist and why it is in such demand. How do data scientists spend their days?
We asked our data science team to weigh in on a typical day in the life of a Resultant data scientist to shed some light on this question.
New Day, New Challenges
As a data scientist at Resultant, there is, in fact, no such thing as a typical day. Each day is full of new, multifaceted challenges. Throughout any given day, the team of data scientists are posed with questions that require their problem-solving abilities to be put to the test. The team thrives in this environment. According to Data Science Practice Manager, Morgan Llewellyn, “It’s what makes us excited to come into the office each day.”
Of course, there are some aspects that hold true day to day such as the approach to problem solving. Recognizing that every data point represents something or someone, one of the team’s top priorities is to understand and internalize the client challenges. This empathetic approach leads to improved, actionable insights for clients.
The hurdles the team must overcome (such as identifying implementable solutions, data quality, methodology, or performance computing issues) are what drives the fast-paced, ever-changing day-to-day activities.
Beginning the Day
Stimulated by challenge, the data scientists like to begin each day by working on their greatest challenge – which varies from researching alternative methodological approaches to strategizing around data quality issues to finalizing the implementation of analytic insights.
“After letting our brains soak overnight, the team is ready to tackle the problem at hand with a fresh perspective,” stated Llewellyn. “It gives me a burst of energy to start out the day solving a complex challenge, especially because the challenge is never quite the same.”
Resolution may take as little as an hour, or up to the full morning, before new code is implemented, or the team develops a strategy around the morning’s challenge.
Any given afternoon may be spent tackling the next challenge, working alongside our clients, conveying results to internal team members, conducting research, brainstorming new solutions, or analyzing and reporting data findings.
Putting Their Heads Together
With a diverse set of backgrounds encompassing economics, physics, network theory, engineering, and more, the data science team works through complex problems by tapping into one another’s unique points of view. On a daily basis, this shows up in their pop-up brainstorming sessions.
More intentionally, the team meets every other week to discuss current projects, develop out-of-the-box solutions, and learn from one another. “Pooling our various backgrounds leads to better results for our clients. Everyone has something to learn and to teach,” stated Llewellyn.
Developing Solutions
“The best solutions are developed when we focus on the client’s need – approaching each challenge from the client’s perspective, determining pain points, and figuring out where to take action,” stated Llewellyn.
While brainstorming, the data scientists work backward through the client’s business process. First, the team formulates potential solutions and evaluates their feasibility using Design Thinking, a problem-solving philosophy and methodology. This solution first process allows the team to dream big and realistically consider what tools the client has at their disposal, which results in an efficient and ultimately successful analytics engagement.
“We believe in failing fast and not just implementing the first solution the team develops,” stated Llewellyn.
Delivering Results
The data scientists will agree the best part about any day is implementing solutions and seeing positive results for clients.
“We don’t stop at good enough. We push ourselves until we have arrived at the best solution for our client,” stated Llewellyn.
Finding the best solution often requires a great deal of creativity, but creative problem-solving is exactly what the team loves.
Conclusion
There is no typical day in the life of a Resultant data scientist. The job demands intellectual curiosity and a desire for continual learning. Our Resultant data scientists are fearless problem solvers who love the challenge each new day brings.
Interested in joining the team? Review open positions for data scientists and more.
