Machine Learning is the most valued skill according to recruiters- Data Science Skills Survey 2022 by Great Learning

As Data Science applications are becoming increasingly popular across sectors, Great Learning, a leading global player in the professional and higher education segment and a BYJU’S group company has released Data Science Skills Survey 2022 to find out different tools, technologies, and skills across categories that are imperative for students and professionals and for an advanced career in the Data Science domain.

Methodology

The report has been developed after primary research through a survey conducted amongst Data Scientists and leading AI/ML practitioners. This was complemented by direct discussions with job-seekers to understand and gauge their perspective on the in-demand skills in this domain. The participants were also interviewed on the critical skills expected by recruiters from professionals of all experience levels while hiring.

Most preferred skills by recruiters

84.4% of professionals mentioned that recruiters look for Machine Learning as the most crucial skill when hiring a Data Scientist, followed by Statistics at 78.9%. 2 out of 3 professionals with 0-3 years of experience said recruiters consider data visualization as a must-have skill. This number reduces for respondents with more years of experience.

Continuous learning is a necessity

As Data Science proves to be a critical proficiency to ensure the company’s development, 98.6% of respondents agree with the need for continuous upskilling in the field. 3 in 4 Data Science professionals with less than three years of work experience engage in upskilling weekly, while more than 50% of professionals in the 3-6 years bracket upskill weekly. Professionals with 6-10 years of experience prefer to upgrade their skills quarterly.

Data Scientists upskilling in Cloud, MLOps, and Transformers to stay relevant

More than 3 out of 5 (61.7%) Data Scientists believe upgrading skills in cloud technologies is crucial followed by MLOps (56.1%) and Transformers (55.0%) to remain relevant to the industry’s current needs. 3 in 4 professionals with 10+ years of experience are learning MLOps to upgrade their skill sets. Mid-career professionals with 3-6 years of experience are learning Cloud Technologies (71.7%) as a core new skill, followed by MLOps (62.3%), Transformers (60.4%), and others.

Sector-wise, professionals in Retail, CPG, and eCommerce are more inclined to learn Cloud Technologies (73.7%) as a new skill.  70.0% of professionals working in BFSI upskill in MLOps. Another 70% and 60% of professionals in the Pharma & Health Sector sector are interested in learning Transformer and Computer Vision a core skill.

Basic skills to make a career in Data Science

As per the survey, 9 out of 10 Data Science professionals mentioned that knowledge of programming language (R, Python, SAS) is among the most basic skills to start a career in Data Science. This is followed by knowledge of statistics (80.6% of respondents) and basic ML (75.6% of respondents). More than 3 in 4 professionals claimed that basic Machine Learning understanding is a must-have skill for a career in Data Science and is indicative of how far we have come in the field.

Popular programming languages amongst Data Scientists

Out of the host of programming languages, 90% of Data Science professionals use Python as their choice for Statistical Modeling. Beyond that, SQL and R are preferred by 52.8% and 38.3% of the respondents respectively. The use of SQL (68.4%) is highest in Retail, CPG, and eCommerce, followed by IT at 62.9%. R is the most commonly used programming language in the Pharma & Healthcare sector, with three in five (60.0%) professionals claiming they use it for statistical modeling.

Top Data Visualization Tools

Despite all the technological advancements in Data Science, the use of MS Excel remains high with 2 in 3 (63.3%) professionals using it regularly. This is followed by Tableau (56.7%), Power BI (43.9%), and QlikView (12.2%). When it comes to experience levels, MS Excel (84.6%) is mostly used by professionals with more than 10 years of experience. Tableau is the preferred choice for mid-senior career Data Scientists with 6-10 years of experience. Sector-wise, Tableau is the most popular tool in Pharma & Healthcare, and IT. Apart from that, MS Excel remains the highest used tool for data visualization in all the other sectors surveyed.

Recently, Great Learning also published the Upskilling Financial Impact Report that highlights the gap in salaries of a professional who upskills and who does not.

Hari Krishnan Nair, Co-founder, of Great Learning said, “The Data Science domain is on track to change the nature of jobs, now and in the future. For professionals looking to thrive in a digital-driven future, setting a foundation for the right Data Science skills needs to start now to weather the changes that are to come. This domain has impacted the way companies and businesses function and professionals who upskill in this field have a chance to become prime candidates in lucrative industries. Through this survey, we aim to help recruiters, industry leaders, policymakers, companies, and Data Science experts/aspirants gain an in-depth understanding of the most impactful languages, models, tools, skills, upskilling approaches, and recruiter perspective that is needed to make structured and informed decisions.