Open since Jul 2026
AVP Data Science
AI Summary
Owns LoopMe's AI throttling system end to end and leads AI products across the business, managing a team of four data scientists and ML engineers while partnering with commercial, operations, product and engineering teams to deliver measurable business impact.
About this role
About LoopMe
LoopMe is an AI company solving one of advertising's hardest problems: making brand advertising actually measurable — and making it perform. Our platform runs patented machine learning models across billions of consumer signals in real time, optimising campaigns toward outcomes like purchase intent, brand lift, and foot traffic rather than proxy metrics like clicks. The result is 2–5x better performance than industry benchmarks, at scale.
We operate a high-load programmatic infrastructure — processing millions of ad requests per second with sub-200ms response times globally. This isn't a layer on top of someone else's stack; it's built from the ground up, in-house, by the team you'd be joining. Founded in 2012 and headquartered in London, we now have 400+ people across 19 cities and have sustained 40% revenue CAGR since 2018. The engineering problems here are real, the ownership is genuine, and the scale is significant.
The opportunity
You own LoopMe's AI throttling system and lead AI products across the business — a senior role combining technical ownership, product ownership, and commercial partnership. You lead a team of four within LoopMe's 17-person Data Science organisation, working directly with commercial, operations, product, and engineering teams and reporting measurable impact to the SLT. The wider Data Science team — led by Chief Data Scientist Dr Leonard Newnham — operates as a single team across London, Poland, and Ukraine, with a track record of publishing award-winning research in automated bidding. This role reports to the Chief Data Scientist.
What you'll do
- Own LoopMe's AI throttling system end to end, covering roadmap, modelling strategy, release planning, measurement and production performance.
- Lead and develop a team of four data scientists and ML engineers, setting priorities and maintaining high technical standards.
- Own the full product lifecycle for AI products, from opportunity identification through launch, monitoring and iteration.
- Partner with commercial teams and clients to understand their needs and coordinate releases with technical and non-technical stakeholders.
- Partner with operations teams to embed AI products safely and measurably into day-to-day business processes.
- Establish clear, evidence-led reporting on progress, risks and measurable commercial impact for senior leadership.
- Develop practical business recommendations by turning ambiguous commercial problems into testable data science questions.
- Manage technical quality by reviewing model logic, system design and code where needed.
What you'll bring
Essential
- Strong commercial experience in data science, machine learning or applied AI, ideally including production systems at significant scale in an adtech environment.
- A track record of owning AI/ML products end to end, from initial idea through production release and measured business impact
- Experience leading, coaching or managing data scientists, ML engineers or closely related technical teams.
- Deep understanding of experimentation, causal measurement, model monitoring and the practical realities of production ML
- Strong Python, SQL and data engineering literacy, with the ability to go deep technically when required.
Nice to have
- Experience with adtech, real-time bidding, DSPs, SSPs, throttling, pacing or auction systems
- Excellent communication skills, able to explain complex technical systems to commercial, operations and senior leadership teams.
- Experience with Google Cloud, Docker, Kafka, Spark, Airflow, ElasticSearch, ClickHouse or similar production infrastructure
- Experience owning product roadmaps, release governance or cross-functional delivery across distributed teams and time zones.
What we can offer
- Bonus
- Hybrid working; meaning you'll spend 3 days a week in our Farringdon office
- 25 days annual leave, plus the Bank Holidays
- 1 month work-from-anywhere
- Annual Wellness Day
- Health Shield; a cash-back health plan for things like dental, optical, physio and wellbeing
- Access to Thrive; accessible mental health support all in one app
- Cycle to work scheme
- Pension
- LoopMe Gives Back Day
- Learning & development support, including internal mobility and bi-annual promotion cycles
To apply
LoopMe does not accept speculative agency submissions. To apply, please use the button below.
Skills
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