At its core, the role of data scientists mainly involves problem-solving. Data scientists follow an iterative process of refining business problems and gathering relevant data to find the most effective solutions for small and large companies. Since data science has penetrated almost every industry, data scientists are in popular demand today.

As an emerging field, data science is an exciting and lucrative career option for those who love to crunch data and mold it into actionable insights. However, the catch lies in knowing where to start and what pathways to choose to build a successful data science career. 

In this article, we’re going to look into the various aspects of a data scientist’s job and take a look at some of the best data science master’s courses on upGrad.

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Who is a Data Scientist?

Data scientists are analytical experts skilled in technology and business science. First, they focus on gathering data for processing and extracting insights. Then, they use their analytical skills and business acumen to find feasible solutions to everyday business problems. 

Naturally, the job demands robust analytical and critical thinking abilities. Therefore, math and statistics are the two core pillars of data science. 

The roles and responsibilities of a data scientist include:

• Collect data from disparate sources, organize, and clean it. 
• Preprocessing of raw data (both structured and unstructured).
• Analyze data using the latest analytical tools and techniques.
• Design advanced models to address modern-day business challenges
• Create predictive models and ML algorithms
• Use appropriate data visualization techniques to present their insights.
• Collaborate with data analysts, data engineers, and the BI team to ideate and develop innovative business strategies.

Skills required to become a data scientist

The job of a data scientist is highly analytical, and hence, the candidate must be skilled in calculations, algorithmic understanding, statistical interpretation, and analytical thinking.

Below are the qualifications that fit the description of a data scientist job:

Educational Eligibility:

• Should have a BA/BSc degree in Computer Science or Engineering 
• Should have a data science diploma or certification
• Should earn a master’s degree in data science or a related field

Other skills:

• Ample experience in data mining and data visualization
• Should understand nuances of operations research and machine-learning 
• Skilled in Python, R, SQL, Java, Scala, Python, and C++ 
• Proficiency in  BI tools (like Tableau) and big data frameworks such as Hadoop
• Must have an analytical thinking approach and strong business acumen
• Highly skilled in math, probability, and statistics 
• Should have excellent presentation and communication skills 

Leading employers for the role of a data scientist

The IT, e-Commerce, healthcare, telecommunications, and banking & finance sectors are the leading employers for the job of data scientists. Companies in these fields often seek to efficiently understand their audience groups’ behaviour to focus on the best offerings and products catering to their customer needs.

Apart from these, the oil & gas and transport sectors are also increasingly capitalizing on big data to positively impact their employees, sales, operations, and target audience.

Some other departments that hire data scientists are:

• NHS
• Government offices
• Research institutions and universities

With the relevant experience, one can even work for a consultancy these days. Consultancies offer more of a client-facing role,  where you will work on projects for a cumulative range of businesses.

Working hours for a data scientist 

Your daily working hours, the balance of work and personal life depends on the type of employer you work for. However, the core working hours are essentially a 10-hour shift ( for example, 10 am-6 pm, or 9 am-5 pm) for five days a week. Despite this, sometimes data scientists may need to work extra shifts beyond regular office hours if a project demands it. 

Today, many organizations worldwide allow data scientists to work from remote locations in a more flexible work schedule.

Best data science courses on upGrad:

Master of Science in Data Science from IIITB 

• Duration: 18 months
• It has more than 60 case studies and projects 
• Timely and systematic doubt resolution sessions

MS in Data Science from UOA 

• Duration: 24 months
• More than 30 live sessions
• One on one feedback and dedicated expert mentorship

Caltech CTME Data Analytics Certificate Program 

• Duration: 7 months
• Offers master classes conducted by Caltech faculty of Engineering and Computers

Professional Certificate – Data Sc. & Business Analytics from University of Maryland

• Duration: 9 months
• Learners get to avail lectures conducted by a top US university

Students get exposed to several capstone projects with all industry experts

Why pursue data science programs from upGrad?

Placement Support:

• upGrad gives access to the world’s most prosperous career portal with almost 5000+ job openings per month.
• The courses here make you interview-ready by giving valuable training, mentorship sessions and exposing you to resume-building tools.
• The information you gather here makes you proficient in making informed choices with the help of career counselling sessions from leading industry experts.

Doubt Resolution

• Data science programs on upGrad provide systematic doubt resolution sessions by industry experts and competent peers.
• The queries asked by students are answered by responses that are verified by experts, which ensures quality learning.
• The mentors give personalized feedback on all projects and assignments submitted by learners.

Learning Support

• UpGrad gives unparalleled guidance through industry mentors, peers and teaching assistants.
• The curriculum comes with one on one personalized feedback on all submissions.

Networking

• The best part about upGrad courses is that they provide Informative sessions that aid in career building.
• There are workshops conducted by industry experts that allow learners to network.
• The curriculum includes interactive group activities to foster peer-to-peer collaboration.

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Conclusion

The bottom line – data scientists are in high demand across multiple sectors. This is so because businesses need technically and analytically skilled people and have enhanced communication skills.

Data scientists predict everything that helps a business grow. For instance, they help a company to understand consumer choices and help them become more environmentally resilient.  As a data scientist, one must find innovative and imaginative patterns to solve problems faced by businesses.

The roles and responsibilities include extracting, analyzing, and interpreting vast data sets from various sources. Then comes the part of making algorithmic calculations, diving into data mining, incorporating machine learning or artificial intelligence, using statistical tools, and finally making an accessible solution for a company. Once data scientists interpret the data, they present the results to the technical and non-technical stakeholders.

The field promises immense opportunities to learn and grow. But, of course, the hefty annual salaries are the cherry on top!