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

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Last Updated on: October 10, 2022

Data science is a mix of programming skills, domain expertise and maths, 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.

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Skills Required To Become A Data Scientist

If you’re thinking about how to start a data science career, know that you need hard skills like analytics, machine learning, statistics, and Hadoop. You’ll also need to hone soft skills such as critical thinking, persuasive communication, and you should be a good listener and problem solver. Of course, you also need data science training. To know more about the various skills you’ll require to become an excellent data scientist click here to read our detailed blog.

This is an industry with a lot of opportunities. Therefore, education and qualifications will get you a job, both now and in the future.

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. 
  • Business Intelligence Analyst: Business Intelligence Analysts use data to identify market and business trends by analysing the data to get a clearer picture of where a company stands.
  • Data Mining Engineers: Data Mining Engineers examine not only their own data, but also information collected by third parties. In addition to data analysis, data mining engineers create advanced algorithms to further analyse the data.
  • Data Architects: Data Architects work closely with users, system architects, and developers to develop blueprints for centralising, integrating, maintaining, and securing data sources using data management systems. 

Data Science Career Outlook

A bright career awaits you in data science, provided you have the right qualifications. It is predicted that the demand for people with data science skills will continue to increase, and those already in data science roles are sure to see their salaries increase in the future. In fact, Data Scientists in the United States earn a yearly average of $1,01,021 and Data Scientists in India earn an annual average of ₹10,50,000.

Statistics from Indeed.com show that there has been a 256% percent increase in the number of data science jobs since 2013.  Also, global data totalled 33 zettabytes in 2018 and is projected to grow to 133 zettabytes by 2025. So, the scope for data scientists is immense, now as well as in the future. 

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.

FAQs

What are the different job roles for data scientists?

A data scientist can be offered various roles in the business organisation. Data Analyst, Data and Analytics Manager, Data Architect, Data Engineers, ML Engineer, Database Administrator, Data Scientist, Statistician and Business Analyst are some of the popular job profiles. 

What are the job responsibilities of a data scientist?

Here are some of the job responsibilities of a data scientist:Extraction of usable data from various data sources.
Work on pre-processing of unstructured data.
Improve data collection processes & methods so that all the relevant information can be covered for building analytic systems.
Analysing large data sets to find trends & patterns for effective decision making. 
Work on building complex systems and algorithms
Share business insights with team members and the wider organisation.
Share solutions and strategies to solve complex business problems.
Collaborate with other teams.

What is the career path of a data scientist?

The data science career path from junior to lead data scientist varies greatly in skills, responsibilities & tasks. An entry-level data scientist is raw, so he mainly works and focuses on developing his core technical skills. The majority of his tasks are focused on producing technical work for his managers. A mid-level data scientist is basically an advanced analytics manager and he knows how to use data science to solve complex business concerns. Lastly, the senior or lead data scientist knows business strategically and is great at understanding business insights and their value. 

What job will I get after completion of the data science course?

Most data science freshers start as data analysts or data engineers. They work on the collection of raw data through the systems. They also work with marketing, sales, customer support & finance teams to help them process data.

Why Choose Data Science For Your Career?

Here are 5 reasons which make data science a highly lucrative career option:Data Scientists are in great demand
There are tons of career opportunities 
It is a highly versatile field and you can work in various industries.
Businesses offer the most important & highest paying designations to data scientists. 
Data science makes you a smarter person as your work involves a lot of problem-solving.

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.

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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