Most-mentioned skills in Data scientist job listings — October 2026

Method

Source: job listings on ROLIVA, which are read from employers’ own careers pages. Only listings confirmed open in the 30 days before the count are included. A listing belongs to this role when its job title matches the same fixed title patterns used for the data scientist jobs page.

How skills were detected: each listing’s description (up to the first 20,000 characters) and any skills the employer lists in structured posting data are matched against a fixed list of 50 skill and tool terms, on whole words. Excel, React, Swift, Spark, Agile are also ordinary English words, so they are counted only in their capitalised product form. A listing counts once per term, however often it repeats it. A mention is not necessarily a requirement, and skills outside the list are not counted.

Timing: the count is repeated daily and this page shows the latest one; the figure kept for each month is the last count taken in that month. Month-to-month changes compare the share of listings, not raw counts, because the number of listings changes.

Limits: these are ROLIVA’s listings only — the employers whose careers pages ROLIVA reads, weighted towards the countries shown above — not the whole job market.

Terms tracked: SQL, Python, Excel, Tableau, Power BI, Looker, dbt, Snowflake, BigQuery, Jira, Confluence, Figma, Salesforce, HubSpot, Zendesk, AWS, GCP, Azure, Kubernetes, Docker, Terraform, React, TypeScript, JavaScript, Node.js, Java, Kotlin, Swift, C++, Rust, Scala, Spark, Airflow, Kafka, GraphQL, PostgreSQL, Machine learning, A/B testing, Agile, Scrum, Stakeholder management, User research, Process mapping, BPMN, UML, Roadmapping, PyTorch, TensorFlow, LLM, Go-to-market.