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How to Start a Career in Data Science: Different Job Profiles & Steps to Become Data Scientist

You are currently viewing How to Start a Career in Data Science: Different Job Profiles & Steps to Become Data Scientist

Data science is a mix of programming skills, domain expertise and math, with the aim of extracting actionable insights from raw data. Analysis techniques and big data collection have become incredibly sophisticated, which explains why data science as a career is thriving.

Organisations today produce voluminous amounts of data that require effective processing, which is driving the growth of the data science market. The data science market in India is expected to grow from $103 million in 2020 to $626 million by 2025, at a CAGR of 43%. The on-campus data science education market is forecasted to reach $386.5 million in 2025, from $48.2 million in 2019, at a CAGR of 42.59%. Needless to say, data science career opportunities have been growing exponentially in the country.

Steps to Become a Data Scientist

A data scientist finds trends and patterns in datasets, communicates recommendations to other teams, creates algorithms and data models to forecast outcomes and incorporates machine learning techniques to improve the quality of data. Below are a few steps that can help you build a career in data science.

Step 1: Earn a data science degree: 

This is not always required but you can consider studying statistics and computer science in order to grasp the basic concepts.

Step 2: Hone the relevant skills: 

It is a good idea to polish a few essential skills, such as programming (Python, R, SQL, SAS), data visualisation and ability to work with tools like Tableau, PowerBI and Excel Big Data. This will, in turn, enable you to process Apache Spark and Hadoop. 

Step 3: Gain experience: 

Pick an entry-level data analytics job to gain experience and build a foundation for your data science career path. You can look for positions of a business intelligence analyst, data engineer, statistician, or data engineer. 

Step 4: Prepare for interviews:

Consider preparing for interviews for a data scientist’s position. It will help you make a confident and knowledgeable impression when you apply for different types of data science jobs. A few questions commonly asked at interviews include the pros and cons of a linear model, using SQL to find data duplicates and the definition of random forest and machine learning.

How to Start a Career in Data Science?

A certified course with 1:1 mentorship, however, is one of the most reliable ways to learn data science. GeekLurn, powered by NASSCOM and IBM Partner, offers a Data Science Architect Program with a 100% placement guarantee. With the program, you will gain expertise in Hadoop Development, Testing, Analysis, Statistical Computing and NoSQL Applications.

You will also be able to work with Real Analytics and master deep learning and machine learning. The course is known for its supportive learning environment, and its highlight includes:

  • 320+ hours of live training session
  • 1.5 years of real-time experience certificate 
  • Scholarships from Day One up to ₹2 lakhs
  • 50+ sponsored fund research projects 
  • Opportunities to gain insights into theories with industry-expert mentors
  • 18 months of sponsored project work at the Authorised Research Centre, funded by IISC, ISB and IIM.

Get the opportunity to be a part of tech talks and webinars from data science heads from Forbes Technology Council and reputed MNCs, along with an opportunity to conduct research work with Singapore-based GeekLurn AI. This course is ideal to build a data science career for freshers, since it does not need any prior knowledge of the field. Students can pay the fees via easy EMIs. You can start paying once you are placed. We also offer a 100% money-back program.

Different Job Profiles of a Data Scientist

Data is taken from different sectors, channels and platforms, including social media, e-commerce sites, healthcare surveys and internet searches. But most of them are unstructured and may require the following professionals for parsing and effective decision making. 

Take a look at the different job profiles if you’ve been wondering is data science a good career:

Data Analyst:

The data analytics industry in India recorded substantial 26.5% year-on-year growth in 2021, with the market value touching $45.4 billion. Data analysts handle complex tasks like processing of massive amounts of data, munging and visualisation. 

Data Engineers:

As of August 2021, data engineers employed in India can command a median salary of ₹12.3 lakhs per annum. The key role is to design and maintain data management systems and make reports and update stakeholders based on analytics.

Data Scientists:

This is one of the top jobs after data science course with a median salary of ₹25.8 lakhs annually. Processing, cleansing and integrating data, automation data collection and collaborating with business, engineering and product teams are among the core responsibilities of a data scientist.

Statisticians:

They are experts in using statistical methods to interpret, gather and analyse data to solve real-world problems. Coordinating with cross-functional teams, designing data collection processes and advising on business strategies are a few important tasks.

Machine Learning Engineer:

An ML engineer can earn between ₹7.5 to ₹8 lakh per annum, on average. These professionals are in high demand today because they have skills in a few of the most powerful technologies like REST APIs. Other roles include performing A/B testing, implementing common machine learning algorithms like clustering and classification, testing ML systems and exploring and visualising data for a better understanding. 

Job opportunities for data science are plenty. Data science can be a lucrative career choice in terms of salary, growth, lifestyle and your future. Taking up the GeekLurn program makes you productive by accelerating and delivering models faster, with minimal errors. With the program, you will be able to deliver AI projects that are bias-free, reproducible and auditable, while offering the best codes, results and reports.

Neel is a Product Manager with an interest in Data Science, Machine Learning, Cloud Computing, DevOps, and Blockchain with expertise in Python, R, Java, Power BI and Data analytics.

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Neel Neeraj

Neel is a Product Manager with an interest in Data Science, Machine Learning, Cloud Computing, DevOps, and Blockchain with expertise in Python, R, Java, Power BI and Data analytics.
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