A Day in the Life of a Data Scientist
It’s a great time to be a data scientist. Technology has advanced to such a level that we are creating massive amounts of data from a variety of sources. According to one report, more data was created in the last two years than the rest of human history and there are no signs of us stopping. Every human being on earth is expected to create around 1.5 megabytes of data every second by 2020. Safe to say, that the job of a data scientist is super important in this tech-savy, digital and data-driven world. Here’s a look at a day in the life of a data scientist.
Task at Hand
The job of a data scientist involves identifying structures, patterns and trends in data that are not immediately apparent. Of course, not all work is done by data scientists alone. The human mind is simply incapable of analyzing the volumes of data we create, and technologies do play their role. Nonetheless, the primary task of data science rests with the data scientist, who must understand business or organizational problems, and use inter-disciplinary approaches to analyze and solve them.
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The job of a data scientist involves working with people from a variety of backgrounds to solve their problems. In an organization, the problems could be many. A data scientist’s day starts off with goal-setting: identifying the most pressing problems to solve on the day or the problems that they can solve to achieve maximum results.
The job of data scientist comprises of extracting data from a variety of sources (reports, reliable databases, inspection records, maintenance records, operations data, customer care data, etc), looking at them, shaping or modelling them and defining approaches to solve their chosen problems. Data scientists work closely with the engineering team to convert their ideas into tangible outcomes like process improvement, fraud prevention, etc.
Programs & Skills for Data Science
The job of a data scientist requires knowledge of programs like R, Python, Tableau, Hadoop & Spark. These programs are dynamic and constantly upgrading. Data scientists are continuously discovering new ways of using these products to push the boundaries of what they can achieve.
It is important for anyone aspiring to get the job of a data scientist to keep up with the latest trends. Data science events and competitions provide great platforms to discover what programs data scientists are using and how. They help data scientists gain fresh perspectives in data problem solving. Data scientists may also read to stay up to date with program updates and new data techniques.
Professionals aspiring to the job of a data scientist generally have a mathematical or quantitative background that helps them reduce their problems to a formula or solve it with an algorithm. Without this background, one may become an expert on certain aspects of data science or programs that help in the data science process but may ultimately fall short in considerations for “real” data scientists.
Anyone aspiring to get the job of a data scientist must, therefore, participate in competitions or take up internships – opportunities that will give them hands-on experience in quantitatively solving problems.
Data Science Research
The job of a data scientist could also cover research. Data scientists also often researchers, who contribute to both – academic and corporate research. The data science team at Facebook reportedly collaborates with universities on a regular basis. Researching data scientists often have the freedom to determine their own projects in organization with sufficient funding to realize them. Moreover, they have the privilege of witnessing the impact of their own research besides publishing it in academic journals.
End of the Day
HBR proclaimed the job of the data scientist as the sexiest job in the 21st century. With the amount of data that we create and the shortage of and demand for data scientists in the jobs market, the proclamation seems easily justified. Data scientists contribute to business and industries in many ways. They help test products, improve processes, and achieve large scale objectives. There is absolutely no doubt that the job of a data scientist will continue to feature in the list of best jobs in the market.