Career as a Data Scientist

Data scientists: Rising alongside the relatively new technology of big data is the new job title data scientist. While not tied exclusively to big data projects, the data scientist role does complement them because of the increased breadth and depth of data being examined, as compared to traditional roles.

What they do? Data scientist represents an evolution from the business or data analyst role. The formal training is similar, with a solid foundation typically in computer science and applications, modeling, statistics, analytics and math. What sets the data scientist apart is strong business acumen, coupled with the ability to communicate findings to both business and IT leaders in a way that can influence how an organization approaches a business challenge. Good data scientists will not just address business problems; they will pick the right problems that have the most value to the organization.

The traditional data analyst may look only at data from a single source – a CRM system, for example – a data scientist will most likely explore and examine data from multiple disparate sources. The data scientist will sift through all incoming data with the goal of discovering a previously hidden insight, which in turn can provide a competitive advantage or address a pressing business problem. A data scientist does not simply collect and report on data, but also looks at it from many angles, determines what it means, then recommends ways to apply the data.

Data scientists are inquisitive: exploring, asking questions, doing “what if” analysis, questioning existing assumptions and processes. Armed with data and analytical results, a top-tier data scientist will then communicate informed conclusions and recommendations across an organization’s leadership structure.
The data movement: Organizations like Face book, LinkedIn, Twitter, are at the heart of the Big Data movement with their users generating loads of information by the second. Latest statistics reveal that we generate close to 2.5 quintillion bytes of data every day, with the data being generated in various forms such as the structured data (surveys, feedback forms etc) and unstructured data (videos, blogs, posts etc). It falls on a data scientist to sift through these enormous amounts of data in its various forms, apply various tools and methods on the data to make sense of it.

Skill set: Statistics; the grammar of data science as one data scientist puts it, is a basic skill. One must be sound in building statistical models and applying statistical analysis to large data sets (read our in-depth Statistics course review). Another skill that is considered basic at the moment is the ability to write code. But with the advancements in technology this may not be required in the coming years. Data scientists should have strong computational and numerical skills. They should also have very strong communication skills - both verbal and visual - along with a very good sense of the business environment. Hence, it needs a diverse skill set.

• Building statistical models
• Applying statistical analysis to large data sets
• Ability to write code
• Strong computational skills
• Numerical skills
• Communication skills (verbal/visual)
• Business understanding

Top qualities: The dominant trait among data scientists is an intense curiosity, a desire to go beneath the surface of a problem, find those important questions and fish out the answers. This probably explains why the word ‘scientist’ fits into this emerging role. Experimental physicists, for example, also have to design equipment, they gather data, conduct multiple experiments, and communicate their results.