Machine learning is the most valued skill according to the survey of recruiters

Data Science Skills Survey 2022 by Great Learning observes the skills most in demand by recruiters

As data science applications become increasingly popular across all industries, Great Learning, a leading global player in the vocational and higher education segment and a BYJU’S Group company, has released a survey on Data Science Skills 2022 to learn about different tools, technologies, and skills across all categories that are imperative for students and professionals and for an advanced career in the field of data science.


The report was compiled after primary research through a survey of data scientists and leading AI/ML practitioners. This was complemented by direct discussions with job seekers to understand and gauge their perspective on the skills in demand in this area. Participants were also asked about the critical skills that recruiters expect of professionals of all experience levels when hiring.

Favorite skills of recruiters

84.4% of professionals mentioned that recruiters consider machine learning the most crucial skill when hiring a data scientist, followed by statistics at 78.9%. 2 in 3 professionals with 0-3 years of experience said recruiters consider data visualization a must-have skill. This number decreases for respondents with more years of experience.

Continuous learning a necessity

While Data Science is proving to be an essential skill to ensure the development of the company, 98.6% of respondents agree with the need for a continuous increase in skills in the field. 3 out of 4 data science professionals with less than three years of work experience upgrade their skills weekly, while more than 50% of professionals in the 3-6 year bracket upgrade their skills weekly. Professionals with 6-10 years of experience prefer to upgrade their skills quarterly.

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

More than 3 in 5 Data Scientists (61.7%) think upgrading skills in cloud technologies is crucial, followed by MLOps (56.1%) and Transformers (55.0%) to stay relevant compared to the current needs of the industry. 3 out of 4 professionals with more than 10 years of experience learn MLOps to improve their skills. Mid-career professionals with 3-6 years of experience are learning cloud technologies (71.7%) as a new core skill, followed by MLOps (62.3%), processors (60.4%) and others.

From an industry perspective, retail, CPG and e-commerce professionals are most likely to learn cloud technologies (73.7%) as a new skill. 70.0% of professionals working in BFSI improve their skills in MLOps. 70% and 60% of pharmaceutical and healthcare professionals are interested in learning Transformer and Computer Vision, a basic skill.

Basic skills for a career in data science

According to the survey, 9 out of 10 data science professionals mentioned that knowledge of the programming language (R, Python, SAS) is among the most basic skills to start a career in data science. Knowledge of statistics (80.6% of respondents) and basics of ML (75.6% of respondents) come next. More than 3 in 4 professionals said that a basic understanding of machine learning is a must-have skill for a career in data science and indicates how far the field has come.

Popular Programming Languages ​​Among Data Scientists

Of the many 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 respondents, respectively. SQL usage (68.4%) is highest in retail, CPG and e-commerce, followed by IT at 62.9%. R is the most commonly used programming language in the pharmaceutical and healthcare industry, with three in five professionals (60.0%) saying they use it for statistical modeling.

Strong points

  • 84% of professionals mentioned that machine learning tracking statistics (78.9%) are the two skills most sought after by recruiters.
  • Python remains the most widely used programming language across all industries; MS Excel, Tableau and Power BI are the top 3 visualization tools used by data science professionals
  • The need for sophistication is universally accepted by data science professionals; 75% of professionals with less than 3 years of experience improve their skills every week

Sam D. Gomez