Best career advice by experts for data scientists

In this article, AIM asks industry experts to share their two cents on how to improve one's career as a data scientist in 2022

According to recent industry trends, the data scientist job market has exploded, with data science being one of the most in-demand jobs. Many colleges are also introducing data science as a completely new programme. This shows that data analysis is already a critical role for businesses today. Data underpins every business decision. Financial organisations, in particular, are personalising customer experiences and combating fraud entirely with the help of data scientists’ important insights and assumptions. Last year, LinkedIn discovered that data analysis is one of the top three fastest-growing career categories, alongside software technology and digital content, which is unsurprising given that data science is expected to be one of the fastest-growing fields in the future. Considering this, AIM has compiled the best career advice given by industry leaders in the field. 

“Aspiring data scientists have a promising future ahead. With the growing demand for data scientists and the current scarcity of skilled professionals in this field, organisations are offering attractive salary packages coupled with a host of other long-term incentives. To be successful, it’s important for data scientists to hone both their business and technical skills. Taking on upskilling courses in data mining and advanced analytics will be an added advantage to building a budding career in this field.” Mr Nirav Choksi, Co-founder & CEO, CredAble,

Read More: Why You Don’t Get Hired As A Data Scientist


Sign up for your weekly dose of what's up in emerging technology.

Tip 1: Understanding the various roles and career options in the industry

Data science is a broad term that encompasses a wide range of topics. Within the field, there are a variety of roles. The following are a few of the most common: 

  • Data analyst
  • Data architect
  • Data engineer
  • AI/ ML engineer 

According to Mr Tridib Mukherjee, Vice President, and Head, AI & Data Science, Games24x7

Download our Mobile App

“Data Science, today, is so pervasive across sectors that it has become an integral part of the product journey. Organisations today not only hire professionals based on their data-crunching abilities, statistical conceptions, or modelling guidelines equipped in the offline or online mode, but also for more intense involvement of statistical analysis, machine learning fundamentals, or other algorithms as part of the product eco-system. These professionals understand the system, the product, the business, and how it all comes together and fits in. One needs to ask themselves what kind of data scientist they want to be.”

Tip 2: Specialisation in the correct domain 

Specialists with extensive knowledge will be better suited to deal with these situations. One of the most crucial questions data scientists have to ask themselves is, “What career is best for me?” 

According to expert Rajiv Kumar, HR Head, Witzeal 

“The demand for skilled data scientists has been steadily pointing northward, particularly for those who can mine and interpret data. Multiple reports predict that India will have over 11 million jobs for data scientists by 2026. One can refer to numerous resources available online, including certification in Data Science (that are much more career-focused) if they want to start their career in data science. These courses provide an opportunity to gain in-depth knowledge about the most advanced skills and techniques like data analysis, machine learning, statistics, Tableau, Python, etc. However, professionals need to focus on developing their critical thinking, problem-solving, persuasive communications, great listening, and domain expertise for better success.” 

Read More: Post COVID-19 Business Model For Data Science Companies

Tip 3: Strong background in mathematics and computer science 

According to Mr Arvind Saraf, Head of Engineering, Drishti Technologies

“The best data scientists are able to solve problems by applying the right algorithms in the right order. That means that there is a big overlap between analytical skills and computer programming knowledge. The modern data scientist has to be able to program in Python, R, SQL and MATLAB. They have to understand databases and distributed systems, as well as probability theory and statistics. And they have to be able to get their hands dirty with a bit of applied math and machine learning.”

Hence, it becomes important that data scientists hold a solid background in mathematics, linear algebra and statistics, including applicability. 

Tip 4: Building relevant industry experience

Mr Gaurav Vohra, Chief Business Officer, UNext Learning, claims that 

“Aspirants need to understand what organisations are precisely looking for in a prospective candidate for the data scientist role. Companies either look for candidates with relevant past work experience as data experts or who’ve worked on real-time projects. The roadmap to becoming successful data scientists in 2022 must focus on building industry-relevant skill sets and getting hands-on experience by working on real-world projects. That will definitely give a boost to their careers.” 

To become a better data scientist, it is essential to build relevant industry experience through internships, projects, and jobs. A lucrative CV helps build connections and attract gainful job offers. 

Tip 5: Never stop learning 

For data scientists, it is key to familiarise themselves with notebooks, pandas, Scipy, and TensorFlow/Pycharm, because these programs can help run quick computations. Knowledge of multiple coding languages, database management systems, data frameworks, libraries, data wrangling tools, and visualisation software allows data scientists to leverage their knowledge for better jobs. 

Dr Venkatesh Sunkad, Dean, “INSOFE School of Data Science”, Vijaybhoomi University, claims 

“Follow the Amazon leadership principle of “learn and be curious”. There isn’t a data science professional who has mastered every skill in the field; let your work guide you towards new skills and always be ready to learn. Pay attention to what makes you feel excited. That’s the key to a fulfilling career.”

Read More: Data Science Career Stories You Loved In 2021

More Great AIM Stories

Abhishree Choudhary
Abhishree is a budding tech journalist with a UGD in Political Science. In her free time, Abhishree can be found watching French new wave classic films and playing with dogs.

AIM Upcoming Events

Early Bird Passes expire on 3rd Feb

Conference, in-person (Bangalore)
Rising 2023 | Women in Tech Conference
16-17th Mar, 2023

Conference, in-person (Bangalore)
Data Engineering Summit (DES) 2023
27-28th Apr, 2023

3 Ways to Join our Community

Telegram group

Discover special offers, top stories, upcoming events, and more.

Discord Server

Stay Connected with a larger ecosystem of data science and ML Professionals

Subscribe to our Daily newsletter

Get our daily awesome stories & videos in your inbox

Do machines feel pain?

Scientists worldwide have been finding ways to bring a sense of awareness to robots, including feeling pain, reacting to it, and withstanding harsh operating conditions.

IT professionals and DevOps say no to low-code

The obsession with low-code is led by its drag-and-drop interface, which saves a lot of time. In low-code, every single process is shown visually with the help of a graphical interface that makes everything easier to understand.

Neuralink elon musk

What could go wrong with Neuralink?

While the broad aim of developing such a BCI is to allow humans to be competitive with AI, Musk wants Neuralink to solve immediate problems like the treatment of Parkinson’s disease and brain ailments.

Understanding cybersecurity from machine learning POV 

Today, companies depend more on digitalisation and Internet-of-Things (IoT) after various security issues like unauthorised access, malware attack, zero-day attack, data breach, denial of service (DoS), social engineering or phishing surfaced at a significant rate.