Data Scientist skills · 59 job postings analysed
Data Scientist skills required in 2026
We analysed 59 data scientist job postings from 27 companies (India, July 2026 – September 2026). The most requested skill is Python, mentioned by 74% of hiring companies, followed by SQL, Machine learning and AWS. Postings that state experience ask for a median of 5 years, and 12% are open to candidates with a year or less.
- 1. Python74% of companies
- 2. SQL70% of companies
- 3. Machine learning56% of companies
- 4. AWS41% of companies
- 5. Spark37% of companies
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From real job postings
Full data scientist skills breakdown
Share of hiring companies asking for each skill
- Python74%
- SQL70%
- Machine learning56%
- AWS41%
- Spark37%
- LLMs30%
- Git30%
- Statistics30%
- Deep learning26%
- Data analysis26%
- Statistical modeling22%
- Google Cloud22%
Soft skills mentioned
- Communication11%
- Problem solving11%
- Teamwork7%
- Stakeholder management7%
Education mentioned
- Bachelor's degree45%
- Master's / MBA39%
- B.Tech / B.E.6%
Of postings that state an education requirement.
Median experience asked
5 yrs
12% open to 0–1 years
Work mode
79% office
Office 79% · Hybrid 2% · Remote 9%
Postings analysed
59
27 companies · India
Top Indian cities
Bengaluru
Hyderabad · Gurugram · Mumbai
Companies in this sample include The Nielsen Company, dunnhumby, Cohere Health, Meesho, NielsenIQ, Gradera Inc., Wabtec, Flywire.
Method: postings collected by the Resumaxx job catalog (July 2026 – September 2026). Skill shares count each company once, so one employer posting many similar jobs doesn't skew the list. Figures describe this sample, not the whole market.
Before you apply
How to tailor your data scientist resume
Usually required
Most companies that mention these list them as requirements. If you have them, make them easy to find.
- Python
- SQL
- Machine learning
- AWS
- Spark
Common differentiators
Frequently mentioned, often as a preference rather than a must.
- LLMs
- Git
- Statistics
- Deep learning
- Data analysis
Industries hiring in this sample: Media, Customer Data Science, Media Measurement, Healthcare, AI, Financial Services.
What makes a data resume match
- Lead with the tools the posting names (SQL, Python, BI tool, cloud) and show each one in a real project.
- Tie every model or dashboard to a decision or metric it changed, not just its accuracy.
- Separate production work from coursework or Kaggle so seniority is clear.
How the match works
- 1. We read the job description and list its requirements, marking each as required or preferred.
- 2. We look for each requirement in your resume and quote the line that proves it.
- 3. A match only counts if the quote is really in your resume. Required skills count double.
Frequently asked questions
What skills do data scientist job descriptions ask for?
In the 59 postings we analysed, the most common were Python (74% of companies), SQL (70% of companies), Machine learning (56% of companies), AWS (41% of companies), Spark (37% of companies). Match these against the specific job description you are applying to, because each employer weights them differently.
How much experience do data scientist jobs require?
Postings that state a minimum ask for a median of 5 years. 12% accept a year or less, and 58% ask for five years or more (based on 40 postings that stated a number).
Are data scientist jobs remote or in office?
Of postings that specified it, 79% were office-based, 2% hybrid, and 9% remote.
How does the job description match score work?
We pull the requirements out of the job description you paste, mark each one as required or preferred, and look for evidence of it in your resume. Only quotes that actually appear in your resume count as a match. The score is weighted so required skills count twice as much as preferred ones.
Should I add every missing keyword to my resume?
No. Add a skill only if you have genuinely used it, and show it inside a bullet about real work rather than only in a skills list. Recruiters and screening tools both treat unsupported keywords as padding.