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What does it take to be a Data Scientist?

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Harvard Business Review declared Data Scientist as the sexiest job of 21st century; IBM predicted that the need for Data Scientists will increase 28% by 2020; Forbes named Data Scientist as the best job in America for three consecutive years; Glassdoor ranked Data Scientist as one of the 50 Best Jobs in America For 2018; Many such researches have already established that Data Science is one of the highest growth career choice today. This has generated a lot of interest among students and professionals and inspired them to follow a career in Data Science. If you are one of those who is intrigued by the opportunities the career in Data Science offers, you should know about the skills that are required to become a good data scientist.

But before we dive in, let’s understand the role of a data scientist. SAS defines Data scientists as a new breed of analytical data experts who have the technical skills to solve complex problems and the curiosity to explore what problems need to be solved. A Data Scientist is responsible for data analysis, a process that begins with data collection and ends with reactive and proactive business decisions made based on analysis results.

A data scientist takes raw data and marries it with analysis to make it accessible and more valuable for an organization. To do this, they need a unique blend of skills – a solid grounding in maths and algorithms and a good understanding of human behaviors, as well as knowledge of the industry they’re working in, to put their findings into context.

A Background in Mathematics & Statistics

For data scientists, a strong mathematics background, particularly in statistics and analysis, is strongly recommended, if not outright required. This goes along naturally with an equally strong academic foundation in computing. This academic background provides you right set of skills that are required for one to become a data scientist. However, this doesn’t mean that Data Science is restricted only to professionals with such academic background; you can easily find people from multiple disciplines like science, arts, business administration etc. pursuing a career in Data Science successfully.

Computer Programming

Data science involves building algorithms for statistical modelling and machine learning hence programming stands to be one of the most important technical skills required for a Data Scientist. Having a strong command of any of the programming languages like R, Python, SQL, Java etc. Helps you use your statistical knowledge to build algorithms and solve business problems.

Quantitative Skills

This is a no-brainer; Quantitative analysis lies at the core of Data Science. It helps you analyze large data sets and get business insights out of it.

Business Acumen

Strong business acumen is one of the key skills required for a Data Scientist. Business acumen can be defined by understanding industry trends, business problems, desired outcomes, competitive scenario, product cycles, business objectives and resources available. One should be able to analyse data and put that analysis into context to find a solution to business problems and come up with right set of recommendations. Domain knowledge of at least one of the industry verticals can give you added advantage and help you analyse real-world problems.

Communication

Communication skills are the most important and most ignored skills for a data science candidate. We always focus on developing technical skills and industry expertise but don’t pay much attention to communication skills. Technical skills like programming and building algorithms can be taught — it is the soft skills that set good professionals apart. Data scientists not only build statistical and machine learning algorithms but also share an excellent rapport with engineers, designers, product managers, operation managers and all business stakeholders in the organization.

Crisp and effective communication is one of the biggest strength of successful data science professionals. No matter how good one is at programming or with industry expertise, the ability to share his knowledge in a convincing manner is what matters. It is not just about the delivering the insights or results effectively, but also listen to the stakeholder’s requirements and understand what the business problem.

What if you don’t meet any/few of these criterions?

You don’t need dishearten yourself if you don’t possess one or more of the skills mentioned above. There are many short term and long term certification programs that can help you develop these skills and start your career in data science. Long-term programs are typically offered by business schools and universities that offer diploma and degrees in data science. Duration of these programs is typically from 6 months to 2 years and is quite a costly affair. On the other hand, short term certification programs come with a steep learning curve and are considerably cheaper with duration as small as 3 days to 3 months.

ScholarsPro offers short term classroom training programs as well as online self-paced programs in data science and machine learning that can help you start a promising career in data science.

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