The field of data science is expanding at a rapid pace all over the world, and India is no exception. As the companies scale and expand, they are looking for experts capable of managing massive datasets, building models on them, and providing actionable insights. While getting relevant experience is expected, employers are looking for much more than a simple certification. There is more that needs to be expected from graduates of Data Science Masters Programs.
Data Science Masters Programs and Industry Expectations
Technical Skills Matter Most
Employers give the most importance to the critical facets of the job. Having a strong command over programming languages like Python, R, and SQL is a must. The candidate should be able to perform data cleaning, data analysis, and data visualization. The basics of data science entail machine learning, deep learning, and statistical modeling. As per a NASSCOM report, the requirement for data science professionals in India is expected to increase by 32 percent every year for the foreseeable future.
Cloud computing skills are also important. Most employers are looking for people who understand how to work with AWS, Azure, or the Google Cloud Platform. Knowledge of Hadoop and Spark, coupled with an understanding of basic big data technologies, is a plus. Also, understanding data pipelines and MLOps can help land some of the best-paying jobs.
Problem-Solving and Business Acumen
Simply possessing technical skills is insufficient. Hiring managers require that candidates possess the ability to solve business issues using the data available. It is important to have a clear understanding of how to take action based on complex data insights. Companies search for candidates who possess a good understanding of the specific problems of an industry.
Being familiar with business intelligence tools like Power BI and Tableau adds more value to a professional qualification. More Indian firms are looking for Power BI professionals who can communicate their findings. Decision makers have more faith in direct and precise presentations of data.
Experience Through Real-World Projects
Hands-on experience matters. Employers prefer candidates with real-world project experience. Internships, research projects, and industry collaborations increase the chances of employment. Participation in open-source projects and competitions on Kaggle will help build your reputation.
Many graduates in data science work with capstone projects. This type of project is meant to provide a way to apply learned skills. Recruiters look out for candidates who employ machine learning algorithms to solve practical challenges.
Soft Skills and Communication
A data scientist must be able to relate to people who have little or no technical knowledge. Communication is everything. Businesses also appreciate professionals who assist the leadership teams in analyzing data.
Teamwork is also important. As with many projects, collaboration is often a requirement. Candidates who are able to integrate with engineers, analysts, and product managers are more suitable for the corporate world.
The Differentiation of Particular Specializations
An understanding of everything is beneficial, but holding a particular specialization always amplifies a candidate’s appeal. Employers value data scientists who specialize in a specific field like finance, healthcare, or marketing. A qualified candidate with risk analytics will be favored by a Fintech company. An eCommerce organization will employ those who understand customer segmentation models.
Specialized programs are being offered by USD Online with its MS in Applied Data Science that has a more defined curriculum. These programs aim to prepare students with skills that are in demand.
Certificates Are Important
Having any form of certification adds credibility. Data engineers and professionals from industries such as Google, AWS, or Microsoft immediately grab the attention of employers. Having the title of a Certified Data Scientist sets the applicant apart from the rest. Other platforms like Coursera and edX also provide these certificates.
Having participated in Hackathons and other coding competitions is a great asset for your CV. Many employers appreciate those who actively solve problems and compete with others.
Predicted Salary Rates in India
There is a lot of variation in what salary can be expected, primarily driven by years of experience and the level of expertise. Data Scientists starting off in India generally receive pay between INR 6-10 LPA. Those more seasoned with 5+ years of experience can expect INR 15-30 LPA. The best-paying employers, including the larger tech companies and startups, offer the best salaries.
Securing a junior role in this ever-evolving job market does not guarantee landing a job. Universities and colleges prepare students for the competitive job market. Employers expect candidates to possess technical competency, problem-solving skills, and hands-on experience. Communication skills, research abilities, and knowledge of the specific field also matter. Graduates of Data Science Masters Programs become preferred employees due to their knowledge and experience.
FAQs
Is a data science master’s degree compulsory for a job in India?
No, but it surely helps. A master’s degree improves job prospects and provides one with a clear-cut structure from which to learn.
What programming languages should a data science graduate be proficient in?
Proficiency in Python, R, and SQL is a must. Familiarity with big data tools such as Spark would be an added advantage.
To what extent is industry experience useful to fresh graduates?
To a very large extent. Internships and real-world projects increase the chances of winning a place in the job market.
Which industries are the best for data scientists in India?
With the plethora of opportunities available to data scientists, most are in the domains of Finance, Healthcare, E-commerce, IT, and many more.
