What Makes A Great Data Scientist
The Harvard Business Review recently described being a data scientist as “the sexiest job of the 21st century.” But what exactly does a data scientist do at work? Here we look at what industry leaders think makes a great data scientist.
Key data scientist skills
The key skill that separates a great data scientist from a great data analyst, engineer or mathematician is programming skills, according to technology journalist Derrick Harris of Gigaom.com. He notes that the ability to test theories and algorithms, by writing bespoke SQL or Python code, allows data scientists to match their knowledge with the requirements of employers.
Orbitz VP of Advanced Analytics Sameer Chopra recommended at the recent Predictive Analytics World (PAW) conference that all aspiring data scientists learn Python now.
Gigaom’s Harris writes that great data scientists need ‘an advanced degree in a quantitative field; hands-on experience hacking data (ideally using Hive, Pig, SQL or Python); good exploratory analysis skills; the ability to work with engineering teams; and the ability to generate and create algorithms and models.’
Chopra stated that if you can do quality analytics across myriad data sources, “you can write your own ticket in this day and age.”
Learning on the hoof
Chopra also noted that you don’t need to back to university to gain the skills required to succeed as a data scientist. He recommends on-line learning and taking part in competitions as ways of picking up skills. Chris Pouliot, director of algorithms and analytics at Netflix, commented at PAW that data scientist candidates with strong skill sets ‘can pick up SQL or Python or whatever you need pretty quickly’.
Making your results accessible
Just crunching numbers isn’t enough! Great data scientists must also be able to communicate the implications of their results by telling a story. While Chopra noted that modern data visualisation tools make displaying statistical results easier, the ability to communicate effectively is essential for any data scientist with a business-facing role.
Communication skills and creativity are also vital for aspiring data scientists applying for jobs. Companies such as Netflix test their candidates extensively and expect them to be able to explain their previous projects clearly and be able to think on the hoof under pressure. Netflix’s Pouliot said that real knowledge is more important than qualifications on a resume, noting that ‘some of the best applicants on paper crashed and burned very early in the (interview) process.’ Pouliot also said that, “creativity is king, I think, for a great data scientist.”
Tips for employing a great data scientist
At PAW Netflix’s Pouliot commented that great data scientists need to feel rewarded by their work. He advised keeping them busy with challenging projects that allow they to express their creativity, and to avoid micro-managing them. He also warned that, in a world where great data scientists are in short supply and receive job offers regularly, paying them the market rate ‘is a good start.’
Netflix employs a team of data scientists that work apart from the company’s other departments. This allows them to focus on their projects and collaborative freely. However, Pouliot did note that embedding data scientists within other departments has its advantages as it leads to ‘a better alignment of research efforts and business needs.’ He suggested that an ideal solution is keep your data scientist team as a unit but to make sure that they are based close to other departments and are available for meetings.
A great data scientist needs to have the skills required to translate raw data into useful results that lead to business benefits, and also the ability to communicate these results to non-statisticians. Data science is an exciting field and a huge growth area. If you have the skills required to make it as a data scientist, or are looking for a great data scientist for your company, then contact us today. We specialise in matching top-quality data scientist candidates to the right position.