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A complete guide to kickstart your career in Data Science

July 25: Data Science has become a growth catalyst for several sectors over the years. It has enhanced business operations and helped organizations make use of humongous volumes of data for better decision-making. The domain’s high demand and the innumerable applications offer career growth beyond conventional roles and have made it a very promising career prospect.

With the onset of the Covid-19 pandemic, Data Science has become an essential tool to tackle real-world problems for varied sectors like healthcare, entertainment, retail, finance, supply chain, transport, and more. Over the years, Data Science has evolved from including only analytics and statistics to powering decisions, predictions, and actions as well. It has equipped us with the scientific capabilities to better anticipate and ultimately affect future outcomes based on past data.

Opportunities in this domain – both applications to the real world and career growth, will continue to grow exponentially. Data Science is ranked #2 among the top 20 in-demand skills, and as per Glassdoor data, 2021 alone witnessed over 37,000 new job offerings for machine learning engineers, data analysts, data scientists, and business analysts, among other roles.

The ever-increasing demand for Data Science experts hasn’t been met given the lack of skilled and industry-ready candidates with a knack for harnessing the power of data. Young professionals are recommended to understand and develop the skills needed for various data science roles so they can tap into this high-demand domain and build a successful career.

Here are some essential tips for starting a career in Data Science:

  1. Choose the right role

Working in the Data Science domain can involve a variety of roles ranging from those of data analysts, data scientists, data visualization experts, data engineers, machine learning experts and more. When starting a career in the datascape, it is critical to take on a role that aligns with your skill set, educational background, work experience and interests.

  1. Update your skill set with courses

After deciding on a role, the next step is to understand it deeper by learning the nuances of that field, which will help you advance in that role. A great way of learning these is to engage with real-world case studies through programs and courses on platforms like Great Learning. The platform presents learning in a unique blended format with live and recorded classes, combining an immersive classroom experience with online learning. The hands-on pedagogy gives learners a chance to gain job-ready skills through projects, assignments, and real-life problem-solving scenarios.

  1. Choose to learn a Data Science tool/language

Selecting tools/languages may be a fundamental problem for Data Science enthusiasts. The answer is to select a mainstream tool/language to start a career in Data Science. To help with this, Great Learning offers an array of certificate and degree programs in Data Science, ranging from basics such as tool/language selection to advanced post-graduate degrees.

  1. Find and join peer groups

Finding like-minded peers who are interested in the same field as you will help you stay motivated and explore more of your potential in the field. Additionally, peers can provide a fresh perspective to your problem-solving efforts, as well as enable networking avenues that facilitate a meaningful career journey. You can find the right peer network for yourself through platforms like Great Learning as well.

  1. Focus on practical applications

Practical and applied learning are more critical than just theoretical knowledge as it allows you to gain practical experience for more meaningful career outcomes. Real-life applications also add to the repertoire of a Data Science professional along with their current skill set. It is only when you start actively contributing with the applied use-cases that your relevance and value creation within an organization is compounded.

  1. Learn communication and soft skills

A Data Science professional may wear multiple hats. Right from exploring the data to get some early insights to modelling for prediction or pattern generation, a lot of critical thinking is required. This is often followed by the ability to better communicate insights to key stakeholders so that they can make informed decisions. To become a well-rounded professional, you also need to develop the right kind of soft skills, such as the ability for critical thinking, listening, persuasive communication, and problem-solving.

Mistakes and Challenges for Data Scientists

Given the various procedures and abilities needed, it is hard for a Data Scientist to avoid making mistakes on their way to a successful career. Some of these mistakes include learning multiple tools/languages at once, not focusing on the fundamentals enough, giving less priority to data visualization and data exploration, not using a structured approach to problem-solving, and most commonly, not staying updated with the trends in the field. These are mostly intrinsic challenges faced by individuals.

From an external perspective, the challenges faced by Data Scientists include collaboration, especially when working on projects. This can pose a serious challenge as a Data Scientist’s job demands them to interact with several individuals simultaneously. They need to analyze large amounts of existing data and often reach a point where they are stuck. It is common for companies to have different stored data structures and inconsistent data formats, which makes it difficult for Data Scientists to validate data. Thus, data integrity is often a challenge from an external perspective.

Job Market and Future of Data Science

Today, the demand for Data Science is vast, with many entrepreneurs investing significant amounts of time and money into it. A job and average salary data repository platform, Indeed, note that Data Scientists in the United States receive an average base salary of USD 141,804 (INR 1,10,89,966) per year, and Indian Data Scientists receive INR 8,24,562 a year. The future of Data Science rests on the dynamic developments in Big Data, Machine Learning, and Artificial Intelligence. These cutting-edge areas give professionals with the latest skills an upper hand in today’s new-age job market, powering their careers with data-driven skills of the future.

Highlighting the brand ethos and pedagogy, a spokesperson from Great Learning said“Quality education with an industry-relevant curriculum is the need of the hour. Great Learning understands the impact of these existing gaps and brings on seasoned board faculty who are passionate about teaching and staying up-to-date with the latest developments. To maximize the learners’ takeaways from their journey with us, we use a mentored learning approach to provide personalized attention to the learners. The modern world needs professionals with industry-ready skills who can unlock the potential of data, and we aim to help build these leaders of tomorrow with a holistic learning approach to unbind each learner’s maximum potential.”

Kickstart your Career with Great Learning

Great Learning, a part of the BYJU’S group, is a leading global ed-tech company for professional and higher education. The platform is on a mission to enable transformative learning and career success in the digital economy for professionals and students across the globe and, to date, has impacted over 5 million learners from 170+ countries.

To know more about Great Learning, please visit:

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