What makes a successful data scientist?


by Vivek Kumar


June 16, 2020

Image credit: salika.co

In the modern data-centric world, companies seek to take full advantage of the use of the data they generate in daily processes. This growing need to access data assets has led to an increase in demand for data scientists. They are able to analyze and process the voluminous amount of data to derive valuable business insights. A data scientist is not only limited to transforming IT systems, but also ready to influence industries, from retail and healthcare to telecommunications, agriculture and mobility, among others.

Undeniably, the field of data science is very broad in terms of skills and roles and covers data analysts, data engineers, database administrators, machine learning engineers, data scientists, data architects, statisticians, business analysts, and data and analytics managers.

The demand for data scientists continues to grow. Based on data from LinkedIn, data scientists ranked as the top most promising jobs in the United States in 2019. They have the ability to help companies interpret and manage data and solve problems complex using their expertise in a variety of data niches. Their roles are becoming increasingly indispensable, even for traditional organizations that previously did not invest a large portion of their budget in technology.

What really defines a Data Scientist?

The role of a data scientist can vary depending on the industries business objectives and goals. He/she must have the ability to understand the business problem or decision which helps to model and summarize what is essential to solving the problem, rather than ignoring that problem. Data scientists have a foundation in computer science, modeling, statistics, analytics, and mathematics, as well as strong business acumen. They are often responsible for data management, analytical modeling, business analysis, and visualizing opportunities for business success.

A data scientist should also have knowledge about designing, developing, and deploying the most relevant solutions for businesses and sharing their findings with stakeholders. Generally, it is someone who knows how to make sense of data and interpret it.

Data scientists work with some of the technology skills, including programming skills in Java, Python, R, and SQL; Reporting and data visualization techniques; Big Data Hadoop and its various tools; Data mining for knowledge discovery and exploration; and communication and interpersonal skills.

Responsibilities:

As data scientists must have academic, technological and business knowledge and skills, their job is simply to evaluate data to extract actionable insights by:

  • Identify issues related to data analysis to deliver the greatest value to organizations
  • Determine appropriate datasets and variables
  • Collect structured and unstructured data from various sources
  • Find new solutions and opportunities by evaluating data
  • Clean and validate data to ensure accuracy, completeness and consistency
  • Analyze data to identify patterns and trends
  • Design and apply models and algorithms for big data mining and more

Become a winning Data Scientist

The buzz around data science has grown tremendously lately and will continue to grow. To become a winning data scientist, a candidate must master data. They must have the ability not only to influence huge amounts of data with sophisticated statistical and visualization techniques, but also to have a dogged insight from which they can derive meaningful insights. While data science is defined as a diverse field that requires programming knowledge along with an understanding of mathematics and statistics, an aspirant must comply with such knowledge and skills.

Certain degrees are advantageous for becoming a data scientist, including applied mathematics, computer science, data management, economics, information technology, mathematics, physics, and statistics.

Moreover, a majority of universities and institutes offer numerous data science certification programs that can help a candidate start their career in this diverse field. Some of the leading data science certifications are UC San Diego Extension School Big Data Certification; Certificate in Data Science from Harvard Extension School; Data Science for Executives by Columbia University; Microsoft Certified Solutions Expert by Microsoft, among others.

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Sean N. Ayres