Data Science Career Path: 12 Demanding & Diverse Roles

A Brief Overview

“Data Science” is the new buzzword among millennials as this multidisciplinary field of computer science offers a wide range of career opportunities. Before getting into the details, let us under what is Data Science. To put it simply, Data Science is an integrative study of data development, identifying patterns and eventually making it an important resource for creating business strategies so a company can stay ahead in the competitive market. It is an amalgamation of data visualization, machine learning, statistics, problem-solving strategies and data analysis. 

Diverse careers in Data Science:

career in data science

  1. Data Scientists are highly qualified professionals who can analyse the type of data to find new solutions, opportunities and also make assumptions on the future of the data. They mostly help in building machine learning models. Statistics show that the demand for Data Scientists is high as there are not enough skilled professionals who can work in this field. With their vivid knowledge, they can experiment with the data trends and make new changes in programming and management. You must have all-round skills like data visualization, understanding probability and can work on various data tools to be a data scientist. The salary of a data scientist is also high; therefore, it is a good career choice in this field.

  2. Most people who are proficient in data analysis start their careers as Data Analysts and then they gradually level up. The main task of a data analyst is to review the data of a given project and identify the strength and flaws. One needs to have skills in programming languages like Python, data visualization and cleaning. This the most chosen career as over time, one can be promoted to a senior data analyst or expand his knowledge and become a professional of an associated field.

  3.  Data Engineering is another coveted career in this stream. The main focus of a data engineer is on software development. An assigned data analyst has the job of evaluating the sales, market performances and report them to the data scientists to fix the issues that can affect the sales or revenue. Knowledge of advanced SQL queries and Python, the capability to build data pipelines are some of the criteria to be a data engineer. With more experience and skill, one can be promoted to a senior Data Engineer.

  4.  Data Architect is an important professional post in the concerned field. If you are into data engineering and have a keen interest in controlling the data storage system of your company, then Data Wire Architecture can be a really good career for you. To get selected as one, you need to have a strong command over SQL knowledge and experience in the management of data and other technical skills based on your specialisation. 
  5. Machine Learning Specialist can be an excellent career choice in the domain of data science. In simple terms, Machine Learning Engineer or Specialist is a data scientist who has specialised in the field of machine learning. Some companies also hire software engineers who can aid in deploying the changes or updates made by a data scientist. One must have a firm grip in Python, Cloud Computing, Spark and basic software engineering skills to work in this field.

  6. Business Analysis is another career option which is in high demand. The foremost task of a business data analyst is to examine current business trends. A business analyst needs to have programming skills and good command in data science along with business skills.

  7.  Quantitative Analysts are experts in data science who mainly focus on statistical analysis where machine learning can be used to figure out financial issues and other market risks.

  8. Become a System Analyst with your knowledge in data science. Solve problems related to administration and organizational by careful examination of problems and send the details to the data scientists to solve them.

  9. One can also become a Marketing Analyst and look over the marketing data to check their effectiveness and also work to promote their products in the market and provide information related to the company’s position in the market. Statistics and studies show that there is an upsurge in career opportunities in the branch of Data Science as it has a promising future. Freelance data experts are also contributing to the growth, popularity, and innovation in this area while simultaneously gaining more experience.

  10. The Database Administrator is responsible for the proper functioning of all the databases of an enterprise. They are also responsible for database backups and recoveries. The data science career path toward database administrator is sought-after.

  11. Another data scientist career path one can take is of a Statistician. They have a sound understanding of statistical norms. They help to create new methodologies and norms for the engineers to apply.

  12. Another path to data science is Data and Analytics Manager. They are responsible for assigning their duties to the team based on their skills and expertise. They develop the data analysis strategies, research and implement the analytics solution, and are also responsible for leading a management team for data analytics.

Explore our Popular Data Science Courses

Top skills required for Data Science 

  1. Statistical Analysis 
  2. Computing 
  3. Data Wrangling 
  4. Programming 
  5. Deep Learning
  6. Data Visualisation 

Top Data Science Skills to Learn to upskill

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How can data science solve real-world problems?

Before a game, a coach can look at the lineup of the other team and run predictive models to see how he might organize his plays to give his team more capability and influence the way the game is played. Data science may be utilized to efficiently enforce laws. Data science tools are being used by law enforcement organizations all around the world to anticipate crimes and prevent them wherever possible. Courses and learning tools may be modified and upgraded to dramatically improve individual student learning results when more historical data on individual students becomes accessible in meaningful numbers. Real-time data monitoring may be used to re-engineer courses to achieve the greatest possible outcomes for students.

How much do Google data scientists make?

Since data wrangling is an essential part of Google's business, data scientists are well paid. Google data scientists make between INR 2,91,512 and INR 73,67,076 per year. The estimated pay is based on 31 Google Data Scientist salary report(s) submitted by workers or calculated using statistical methods. When bonuses and other incentives are taken into account, a Data Scientist at Google can expect to earn INR 14,30,896 per annum. However, the typical salary for data scientists in Google may vary depending on years of experience, education, and location. Google recently posted a job opening for a data scientist who could use operations research and statistical approaches to tackle issues relating to storage, network, and data center capacity for both internal services and the Google Cloud Platform.

What is the most attractive part of being a data scientist?

Data scientists uncover useful patterns and insights by combining vast volumes of data in novel ways to optimize corporate operations, identify opportunities utilizing research and management tools, and reduce risks. Data scientist brings skill sets and expertise from diverse backgrounds such as mathematics, statistics, analytics, modelling, and business acumen, and has already been dubbed the trendiest career. These abilities enable them to spot trends that might aid the company in identifying new market possibilities.

Who are the top employers in the field of data science?

The top employers in the field of data science include IBM, Google, Uber, Flipkart, Facebook, and Fractal.

What is the average salary for a data scientist?

The average salary for a data scientist is 10.0 lakhs per annum.

What is the average salary for a statistician?

The average salary for a Statiscian is 4 lakhs per annum.

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