AI, Analytics and Technology-centric Talent for businesses turning content, audience, and data into competitive advantage.
Content recommendation engineering, audience intelligence data science, streaming analytics, advertising measurement, and digital marketing analytics — Burtch Works connects entertainment and media organizations with the specialists shaping the future of media across every data discipline.
The media organizations staying ahead of disruption are the ones who hired for it first.
Generative AI, streaming platform proliferation, and audience measurement fragmentation are reshaping the entertainment and media landscape faster than most organizations can staff for it. The challenge isn't understanding that disruption is happening — it's having the data and technology talent deployed across every function that the disruption touches.
That means ML engineers who can rebuild recommendation architectures around foundation models rather than collaborative filtering, data engineers who can unify audience measurement signals across streaming, broadcast, digital, and social data environments that weren't designed to talk to each other, data scientists who can model audience behavior at the scale and speed modern media platforms demand, and digital marketing analysts who can connect content performance data to audience acquisition and monetization strategies in an environment where attribution is increasingly contested. It also means product managers who can translate what ML systems are capable of into product decisions that serve audiences and advertisers, and technology professionals who can build and maintain the platform infrastructure that media data operations run on.
Burtch Works has built deep relationships with talent across all of these disciplines in entertainment and media for 15+ years. When speed and domain depth both matter — and in media they always both matter — that's the difference between a hire and a search that runs out of candidates.
RECOMMENDED SOLUTIONS - ENTERTAINMENT & MEDIA
Tailored for the Entertainment & Media operating environment.
Whether you need a senior analytics leader deployed within the week, a full managed delivery team, or a strategic advisory engagement — we have the right path for your timeline and structure. Designed and built to move at your industry's pace.
Specialized Analytics Talent Search
Contingency and retained placement of content recommendation engineers, audience data scientists, streaming platform analytics leads, and advertising measurement specialists.
Retained Executive Search
Dedicated search for VP Analytics, Head of Audience Intelligence, Director of Content Analytics, and senior data science leadership in entertainment and media.
Fractional Analytics Leadership
Deploy experienced media analytics executives on a fractional or interim basis during platform transitions or critical leadership gaps.
Staff Augmentation
Specialized ML engineers and analytics practitioners for recommendation system development, audience measurement buildouts, and advertising analytics sprints.
RECRUITER & TALENT INTELLIGENCE - ENTERTAINMENT & MEDIA
What the market is telling us about analytics and AI talent in entertainment and media -- right now.
1 in 8
New Technology, Media & Telecommunications job postings now require AI skills—the highest hiring intensity of any industry.
PwC 2026 Global AI Jobs Barometer
85%
Of organizations expect to deploy autonomous AI agents within the next three years.
Deloitte State of AI in the Enterprise, 2026
60%
Of workers now have sanctioned access to Generative AI tools—up 50% year over year. demand.
Deloitte State of Generative AI 2026
63%
Media and telecommunications CEOs expect Generative AI to fundamentally change the way their companies create value within three years.
PwC Global CEO Survey 2026
MARKET SIGNALS - ENTERTAINMENT & MEDIA
The ML engineers who built yesterday's recommendation systems aren't automatically qualified to build tomorrow's — and the market hasn't caught up.
PwC's 2026 Global AI Jobs Barometer identifies Technology, Media and Telecoms as the sector with the highest AI hiring intensity — with nearly one in eight new roles now AI-related. Within media, the most acute talent gap is in recommendation engineering: the shift from collaborative filtering to foundation-model-augmented personalization requires LLM deployment experience that most traditional media analytics candidates simply don't have. Organizations that are evaluating candidates against 2022-era competency frameworks are systematically misidentifying their shortlist.
Major streaming platforms are paying compensation premiums that traditional entertainment organizations can't match through base salary alone.
The compensation gap between major streaming platforms and traditional entertainment organizations for senior analytics and ML talent has widened significantly since 2024. Platform companies are offering total compensation packages that include meaningful equity, recurring bonus structures, and AI research exposure that broadcast and studio organizations structurally can't match on base salary alone. Without a strategy for competing on mission, culture, or domain specificity, traditional entertainment organizations will continue to lose the best candidates to the platforms they're trying to differentiate against.
Cross-platform measurement fragmentation is creating a new analytics leadership profile that most media organizations haven't formally defined yet.
The breakdown of single-panel audience measurement and the proliferation of streaming, digital, and social data environments has created demand for analytics leaders who can architect unified measurement frameworks across incompatible data sources. This is a role that didn't formally exist in most media organizations three years ago. The candidates who can do it are rare, are being actively recruited by measurement technology companies, and require a hiring brief that specifically describes the cross-platform architecture challenge — generic analytics director searches don't surface them.
Programmatic AI is creating an analytics talent requirement in media that sits at the intersection of adtech, ML engineering, and commercial strategy.
AI-driven advertising measurement, attribution modeling, and yield optimization are creating demand for a new category of media analytics practitioner — one who understands programmatic advertising mechanics alongside ML engineering. Most analytics recruiting processes don't screen for the adtech domain knowledge this combination requires. The organizations that hire against the combined profile fill the role with candidates who contribute immediately. Those who hire against generic data science criteria fill it with candidates who take six months to become effective.