London Data & Analytics: Python, SQL, AI Lead 1,468 Roles -- December 2025
BetaAmong tracked employers, London's data hiring in December 2025 recorded 1,468 roles across 878 companies. Professional Services led at 18% of tracked postings, while AI and Machine Learning grew +3.0pp to 11%. Remote work led working arrangements at 53% of direct employer postings, with an overall flexibility rate of 86%.
This report analyzes 1,468 Data & Analytics job postings from 878+ companies tracked via direct employer career pages and job board aggregators. Our coverage skews toward tech-forward and scaling companies; large enterprises using enterprise hiring platforms may be underrepresented. Coverage varies by section and is noted throughout.
Key Takeaways for Job Seekers
Skills Demand
67% of roles with skills data
Skills insight: Python (35%) and SQL (33%) remain the core skill pair, co-occurring in 18% of tracked roles with skills data. AI (15%) and Machine Learning (13%) are the next most common, reflecting the growing integration of AI across data functions. AWS leads cloud platforms at 11%, followed by Azure (8%) and GCP (6%). The modern data stack is represented with dbt (8%), Snowflake (7%), and Airflow (6%). PyTorch at 7% and LLMs at 6% indicate growing demand for deep learning and generative AI capabilities.
Seniority Distribution
Junior: 0-2 years | Mid-Level: 3-5 years | Senior: 6-10 years | Staff/Principal: 11+ years (IC track) | Director+: Management track
Biggest Gainer
Senior
+3.5pp
Biggest Decline
Director+
-4.1pp
Senior-to-Junior Ratio
8:1
Senior+ roles per Junior role
Entry Accessibility Rate
28%
Junior + Mid-Level roles combined
Senior roles account for 55% of tracked postings, up +3.5pp from November. Director+ roles saw the largest decline at -4.1pp, dropping to 7%. The 8:1 senior-to-junior ratio positions London as more accessible than the US markets tracked. Entry accessibility at 28% (junior 9% + mid-level 19%) is the highest among tracked cities, providing a moderate pipeline for early-career candidates.
Working Arrangement
Onsite: office full-time | Hybrid: mix of office and remote | Remote: work from anywhere | Flexible: employee chooses arrangement
93% of direct employer postings with known working arrangement
Among 349 direct employer postings with classified working arrangements, remote leads at 53%, followed by hybrid at 21%, onsite at 14%, and flexible at 12%. The combined flexibility rate of 86% positions London's tracked data market among the more flexible of tracked cities. However, 30% of UK companies plan to require five-day office attendance by 2026 (Fair Play Talks, October 2025), which may shift this balance. Currently, over 40% of UK workers spend at least part of their week working remotely (IT Desk UK, 2025).
Role Specialization
Biggest Gainer
Data Engineer
+4.5pp
Biggest Decline
Data Architect
-6.4pp
ML Engineer and Data Engineer each account for 22% of tracked roles, together representing 44% of all demand. Data Analyst follows at 18% and Data Scientist at 16%. Data Engineer grew +4.5pp month-over-month, the largest role share increase, likely reflecting continued investment in data infrastructure. Data Architect declined -6.4pp to 6%, which may indicate seasonal slowing in governance-focused hiring.
IC vs Management Track
Individual contributor roles account for 92% of tracked postings, with management at 8%. This IC-heavy split is typical of data and analytics functions where technical execution remains the primary hiring need. The 8% management share is slightly below the 10% average across tracked cities.
Compensation
Compensation data excluded due to low disclosure rates in markets without pay transparency legislation.
Market Context
Methodology
This report analyzes direct employer job postings for Data & Analytics roles in London during December 2025.
Data collection:
- 1.Over 1,400 roles from 878+ employers aggregated from multiple sources
- 2.Recruitment agency postings identified and excluded (4% of raw data)
- 3.Jobs deduplicated across sources to avoid double-counting
Classification:
- 1.Roles classified using an LLM-powered taxonomy
- 2.Subfamily, seniority, skills, and working arrangement extracted
- 3.Employer metadata enriched from company databases where available
Limitations:
- 1.Not a complete census of the market - some roles may not be captured
- 2.Skills analysis based on 982 roles with skill data (67% coverage)
- 3.Salary data not included due to low disclosure rates
- 4.Working arrangement based on 349 direct employer postings (Adzuna excluded)
Data coverage:
80%
Seniority coverage
Roles with seniority level classified
93%
Arrangement coverage
Roles with working arrangement known
67%
Skills coverage
Roles with skills extracted from description
60%
Employer metadata
Roles with enriched company data
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