Burtch Works 2025 Artificial Intelligence and Data Science Compensation Report

Burtch Works is a U.S.–based talent partner that fuses 15+ years of analytics recruiting expertise with today’s most in‑demand AI skill sets—delivering specialized teams and measurable outcomes.

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Recognized as one of the Fastest‑Growing Staffing Firms in the United States.

‍Burtch Works provides Talent Solutions and Managed Services across Artificial Intelligence (AI), Data Science, Analytics, Machine Learning, Data & Cloud Engineering, Cybersecurity, Product, Technology, and Market Research. With domain depth, national reach, and curated networks, we meet organizations anywhere on the AI journey—from first hire to fully scaled teams.

Our 2025 Compensation Report delivers up-to-date salary benchmarks and market trends, arming talent leaders and job seekers with the data and insights to pursue value-driven opportunities and sustainable ROI.

_{Salary & Market Intelligence to Win the AI & Data Science Talent Race}

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In today’s hyper-competitive market, CHROs, CTOs, CDOs, and Heads of Insights face unprecedented pressure to secure high-impact Artificial Intelligence (AI) and Data Science talent who can drive transformation, streamline operations, and deliver measurable ROI.

The Burtch Works 2025 Artificial Intelligence & Data Science Compensation Report—built from proprietary, first-party data gathered from over 470 validated professionals across industries—equips executive teams and job seekers with clarity, credibility, and competitive intelligence to make confident hiring decisions. Inside, you’ll find:

Up-to-date salary benchmarks for AI & DS roles at all levels.
Market trends and talent insights to refine recruiting strategies.
Competitive compensation data to attract and retain top performers.
Guidance on Gen-AI, Machine Learning Ops, and Retrieval-Augmented Generation upskilling paths.

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Why Salary and Industry Insights Matter in 2025:

As AI adoption accelerates and cross-disciplinary skill demands rise, employers must modernize compensation models and hiring practices. This report empowers you to:

Evaluate internal pay equity and external competitiveness.
Align budgets with strategic compensation planning.
Identify emerging job titles and in-demand skill sets.
Make timely, evidence-based hiring decisions.

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In a year defined by rapid change, redefining your AI talent strategy, launching a data-driven transformation initiative, or refining executive hiring frameworks, Burtch Works delivers the data and foresight to help you build, retain, and future-proof your AI and Data Science teams.

AI & Data Science Hiring Landscape

The Great Grad Reset

The entry-level market is the toughest in a decade. Savvy companies are acquiring graduates for entry roles that skew towards AI-Ops/evaluation, making internships and hands-on portfolios a decisive hiring signal.

Moving Gen-AI From Pilot to Production

Enterprise-level organizations are moving beyond experimental trials of generative AI applications to full-scale, real-world deployments. Consequently, hiring has transitioned from “prompt roles” to Applied Large Language Model (LLM) Engineers who can integrate, monitor, and optimize costs of actual workflows.

Reinforcement Learning from Human Feedback

RLHF and Alignment AI remain supply-constrained, with job requisitions up +34%, surpassing supply at +7%. Scarcity will continue to drive premiums and push teams toward train-to-hire pipelines and selective offshore/nearshore augmentation.

Turning AI Labs into Go-to-Market Machines

AI Innovation labs are quickly transforming into productization engines, managing reference architectures, governance, and sprint pods that convert proof-of-concepts into shipped, ROI-tracked features. The fastest to market wins the race to meet complex customer expectations.

Talent Searches Tilt Toward Individual Contributors

Firms favor high‑leverage ICs who can ship proof-of-concepts quickly, minimizing operational overhead to gain maximum efficiency and ROI.

2025 Talent Market: Operational AI, Built to Ship

Individual Contributor Hiring Surges to Productize and Prove ROI

AI has moved from pilots to platforms—standardized, governed, and cost-disciplined. Hiring now centers on applied builders and ops-savvy leaders (DS, ML, MLOps) who can ship, monitor, and scale. As organizations pivot from exploration to measurable, production delivery, Data Science and AI pay bands are converging, reflecting outcomes over experiments. Hiring is now focusing on selective expansion and Individual contribution-first teams.

When compared to 2024, teams grew modestly in 2025—median pod size increased from 3 to 4 roles, —favoring individual contributors with lightweight management layers for faster cycles and clearer ROI.

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