In recent years, the volume of big data has tremendously increased which requires that we turn it into useful information. Data Science combines the best of Mathematics, Computer Science and Business to extract insights out of structured and unstructured data. Data science skills are in high demand across industries. This article helps you answer basic questions like – what is a Data Scientist? What are its scope and roles? And how can you become one?

What is a Data Scientist and what do they do?

“A data scientist is that unique blend of skills that can both unlock the insights of data and tell a fantastic story via the data. – DJ Patil”

Data Scientists draw business insights and predictive forecasting from structured and unstructured datasets. They combine Applied Mathematics, Programming and Domain expertise knowledge to build end-to-end solutions to complex business problems. 

The Venn diagram here shows the scope and nature of a Data Scientist’s work. 

Venn Diagram depicting the knowledge scope of a Data Scientist

The white area indicates what is a Data Scientist’s role and what are the skills needed.

It is the intersection of all the 3 major pillars of Data Science – Programming, Math (Statistics) and Domain knowledge.

The role overlaps with those of a Statistician, Business Analyst, and Data Engineer. They analyze, process, model, interpret and visualize extremely large amounts of data. They use this information to draw hypotheses, make inferences, analyze business and customer trends and define business processes. It is one of the highest-paying tech jobs for 2020.  

Is Data Science for you?

What is a Data Scientist’s role and skill you are most interested in?

Are you a good fit for Data Science?
Well, you are if you:

  • Hold a degree in Mathematics, Statistics, Computer Science, Management or Research field
  • Analyze information in all the work you do
  • Can solve any problem with programming.
  • Enjoy applying Mathematics and Statistics to infer solutions
  • Understand business and customer needs
  • Have a positive attitude towards problem-solving and practice with critical thinking
  • Communicate in business language to visualize your data in a cross-functional team

The good part is, Data Science is a diverse field that has scope for all skilled professionals. Let’s get to know the types of industries that are looking for Data Scientists?

Industries that require Data Scientists

Reliable data is an integral part of every sector. Each industry requires skilled Data Scientists to extract information out of complex data to meet their business expectations. Data Science is a diverse field with a distinct balance of various skills, it adds value to all and is more critical to BI and AI industries. Industries that are in huge demand for Data Scientists are – IT, Healthcare, Telecommunication, Weather forecasting, Research, Finance & Insurance, Manufacturing, Banking, Aeronautics, E-commerce, Energy sector, and Public sector, etc. A research conducted by IBM shows the greatest demand for Data Science and Analytics (DSA) jobs is in Finance & Insurance, Professional Services, and IT.

Image credit: IBM Quant Crunch

The research also revealed that the finance industry offers significantly higher pay for DSA jobs than other industries.

Data Scientist Job Description

So what is a Data Scientist’s job responsibilities? They acquire deep knowledge and provide high-level solutions to the tasks of a Data Engineer, Statisticians and Business Analysts.

Let’s summarize the job descriptions:

  • Identify new methods to test product changes, run A/B tests, perform statistical analysis and draw conclusions on the impact of your models for future trends.
  • Prototype solutions to complex business problems and build processes and models from aggregated data both structured and unstructured.
  • Develop and implement frameworks and processes for systematic and automated data analysis and make them Machine Learning ready
  • Build Data pipeline tools, Machine Learning, and Statistical models and algorithms to be implemented by Statisticians, Data Engineers, and Data Analysts.
  • Visualize and interpret the results of analyses, and create strategy recommendations in a cross-functional team.

Requirements to Become a Data Scientist

Depending on the industry, a Data Scientist’s role may have a different inclination towards basic technical, analytical and domain skills. So, what is a Data Scientist’s basic skills to begin with?

1. Educational background

Degree in a quantitative field (e.g., Computer Science, Economics, Engineering, Mathematics, Finance, Statistics, Operations Research, Physics). A Master’s or Ph.D. is generally a plus.

2. Skills

Broadly classified into Statistics, Programming and Domain expertise-

Image Credit:

3. Math and Statistics

To project your data you need Statistical and Mathematical knowledge (Linear Algebra, Calculus, Metrics and Probability). Learn some popular tools like R, SAS, and/or Tableau.

4. Programming (Database)

You need Computer Software Programming and coding skills to/for:

  • Process your data by developing tools, Data Science models and Algorithms by coding in Perl, Java, Python, and R or Scala
  • Design, Manage, and Backup Data: RDBMS: Hadoop 
  • Query large datasets: SQL and NoSQL
  • Containerize: Kubernetes and Docker
  • Version Control: Git and GitHub
  • Cloud Server Architecture: AWS
  • Build ML Algorithms: You need Data science concepts such as Machine Learning, Databases, Data mining, Data Engineering, Visualization, and Predictive modeling.
    • ML techniques: K-nearest neighbors, Regression, Naive Bayes, and random forests, etc.
  • Data Science tools and frameworks: Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark
  • Computer Science fundamentals: Data Structures, Algorithms, Performance complexity, and implications of Computer Architecture (I/O and memory tuning).

5. Domain knowledge

Good enterprise expertise helps you build better ML model tools and processes and infer the best business decisions.

6. Communication and Presentation

Data Scientist communicates complex ideas to business stakeholders with easy to understand data visualizations.

7. Strong portfolio

A CV is your professional summary to project, what is a Data Scientist’s role that you most fit in. Link real-time projects to show the problems that you can help resolve from GitHub, Kaggle, LinkedIn, or KDnuggets.

Data Scientist Salary

“Data scientists are in great demand worldwide, and due to the shortage of skilled professionals, salaries are high – Professor Richard Davies, Pro-VC”
The median salary for a Data Scientist is 10 lakhs and shoots up based on experience, location, and tool expertise.

“In the digitized economy, the competitiveness of companies and entire economies is increasingly driven by data-based innovations. But without data scientists at companies, data remains largely worthless.  – Dr. Alexander Börsch, Head of Deloitte Research”

A Data Scientist has good domain knowledge, an expert in Data Science concepts, Coding, Mathematics, and Statistics. 

Are you ready to transition your career into Data Science? The Springboard Data Science Career Track is a self-paced, 1:1 mentoring-led and project-driven program that comes along with a job guarantee. This provides a structured path from building your Data Science concepts to writing an impressive CV and interview tips.