Who is a Data Scientist? What do they do? – Job Description


Data science is not only about processing and interpreting data to build innovative business solutions. It combines mathematics, statistics, computer science, and information science to capture, process, analyze, and maintain data and communicate their findings. As such, data scientists gather data from disparate sources, clean and organize it, and analyze it to find hidden patterns and trends. The next step is to effectively visualize the patterns in ways that are comprehensible to both technical and non-technical members of an organization. Business executives use these trends to make data-driven and actionable decisions. 

Essentially, a data scientist’s job description is about solving real problems of a company based on real-time data, using a diverse combination of advanced tools, concepts, and algorithms.

Since data is used by all industries now, the role of a data scientist is becoming increasingly important across all sectors. In fact, data scientists and related roles make for a significant percentage of job postings across platforms like LinkedIn and Indeed. 

Leading employers for the role of Data Scientist

The IT, e-commerce, retail, marketing, and banking & finance sectors are the leading employers of data scientists and data analysts. Companies in these fields often harness data with an aim to understand their target audience’s behaviour, needs, and pain points and develop innovative solutions to cater to them. Apart from these sectors, oil, gas, telecommunication, and transport are also capitalising on big data to create personalised solutions for their target users.

Some other departments that hire data scientists are:

  • NHS
  • Government offices
  • Research institutions and universities

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The roles and responsibilities of a data scientist

Data scientists are data experts with highly advanced tech skills to process, analyze, and interpret large volumes of complex data. Their job is to identify a company’s key problem areas and dig deep into data to find answers to relevant questions and drive innovation. They are master data communicators with excellent analytical abilities who focus on delivering tangible results. 

Data Scientist roles and responsibilities include:

  • Identify credible sources to harness data in large volumes.
  • Building predictive models and advanced ML algorithms. 
  • Perform data investigation and exploratory data analysis to verify data.  
  • Presenting findings through appropriate data visualization techniques.
  • Work closely with data engineers, data analysts, and BI analysts to find and propose effective solutions to business challenges. 

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Skills and qualifications required to be a Data Scientist

The following are the eligibility criteria that fit the data scientist job description:

Educational qualifications:

  • Must have a BSc/BA degree in the field of Computer Science/ Software Engineering/Information Science/Mathematics.
  • Must have a postgraduate degree/diploma certification in Data Science/Machine Learning.

Other requirements:

  • Documented experience of being employed as a Data Analyst or Data scientist in a reputed organisation.
  • Ample experience in data mining and data visualisation. 
  • Proficiency in SQL, Python, R, Java, C++, and Scala. 
  • Expertise in using intelligence tools like Tableau and big data frameworks like Spark, Hadoop, Cassandra, etc.
  • Must possess a problem-solving and analytical thinking attitude. 

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Working hours of a Data Scientist 

Typically, a data scientist’s working hours and work-life balance depending on the employer organisation. While the usual working hours include a 9-10 hours shift, five days a week, they may be required to work extra on high-priority and time-sensitive projects. Data scientists work in an office environment and some companies even allow them to work remotely. 

How much does a Data Scientist earn?

The salary of a data scientist depends on their work experience. For freshers, the salary ranges between 4-7 lakhs per annum. With seasoned experts, it can grow up to 15 lakhs per annum and beyond. Apart from CTC, data scientists also enjoy various other benefits, including pension schemes, performance and retention bonuses, medical and life insurance, etc. 

Factors like the company location, educational qualifications, and business sector determine a data scientist’s salary. What’s most exciting about a data science career is that it offers tremendous learning and growth opportunities. 

Work Experience required to be a Data Scientist

Before you start a full-time job as a data scientist, you can try for internships in reputed firms. You can do this right after completing your bachelor’s course. If you have the right skills and qualifications, you can end up bagging entry-level roles in small to medium enterprises.

Apart from internships, platforms like Topcoder and Kaggle host coding and data science hackathons. These competitions are ideal for identifying emerging talent. In addition, you must also actively lookout for data science and tech conferences/events. These are excellent opportunities for networking and expanding your industry knowledge. Who knows, you might even attract the eyes of a potential employer in such events!

Career growth of a Data Scientist

A data scientist’s career growth is based on how quickly one can learn the relevant skills required to analyze and interpret large data sets. The growth ladder starts from being an associate data analyst and goes up to the role of the chief data scientist. After that, the first promotion goes up to senior data science roles within the company, mainly involving the management and supervision of junior data scientists and analysts. 

The average time in which one can expect to be promoted is 2-5 years, depending on the performance. After five years, you can upgrade to senior-level roles in a company. 

Data scientists can also launch their startups after gaining enough experience. There’s a booming market for AI/ML-based apps and services. If you love academia, you can transition to more research-oriented data science roles. 

Master Data Science with upGrad

If you’re passionate about becoming a data scientist, upGrad has a whole range of data science courses suited for both freshers and professionals. You can check out some of their top courses – Master of Science in Data Science (LJMU), Professional Certificate Program in Data Science for Business Decision Making (IIM Kozhikode), and Advanced Certificate Programme in Data Science (IIIT Bangalore). 

Taught by expert instructors of top institutes, these courses will help you gain mastery over theoretical data science concepts while also encouraging you to work on real-world projects. All students receive 360-degree career assistance, dedicated mentorship, and placement opportunities with established firms in the country.

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By now, the importance of data scientists in the present economic scenario must be pretty clear to you. From understanding consumer choices to how the company can be more environmentally resilient- a data scientist’s job revolves around finding patterns that solve the issues faced by any business in the most imaginative and innovative ways. Thanks to growing industry demands and the stark shortage of skilled data science professionals, you can easily earn a seven-figure salary as a data scientist.

The bottom line- there’s plenty of growth opportunity in this field. So, get a data science degree and shoot for the stars!


What is one skill that a data scientist mandatorily needs?

Machine learning is one core skill you must have as a data scientist. This skill is needed to build predictive models for solving a company's problem. You need to fit algorithms into machine learning to predict a future possibility for the companies based on past data.

Can I become a data scientist on my own?

To become a data scientist, you must have professional education qualifications from recognized institutions. However, you can acquire additional skills to enhance your ability as a data scientist. For example, you can take online classes for coding or programming languages like SQL, Java, or python. You can also opt for associate diplomas.

How long does it take to learn data science from scratch?

The ideal time is a 2-3 year entire time course. However, some boot camps have been conducted that take as little as 12 weeks to give you essential insights on data science. By attending these boot camps, you can become a neophyte data analyst and land up in assistant roles in the data analysis department of companies.

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