Head of Data Science & Applied AI

Prolific
London
9 months ago
Applications closed

Related Jobs

View all jobs

Principal Data Scientist & Machine Learning Researcher

Head of Machine Learning (Recommendations, AI Stylist & Search)

Data Scientist – GenAI & AI Engineering

Lead Machine Learning Engineer, AI

Head of Data Science

Head of Data Science

Prolific is not just another player in the AI space – we are the architects of the human data infrastructure that's reshaping the landscape of AI development. In a world where foundational AI technologies are increasingly commoditised, it's the quality and diversity of human-generated data that truly differentiates products and models.

The Role

Lead the technical team that's revolutionising how AI learns from humans. At Prolific, you'll build and direct the data science and AI/ML engineering function that powers the world's leading platform for human feedback collection – enabling AI developers to efficiently incorporate human intelligence into their models. Your team will solve challenges across the full ML/AI spectrum: creating intelligent systems that optimize feedback quality, design behavioural modeling at scale, and developing breakthrough methods for effective human-AI interaction. This isn't just another technical leadership role; you'll directly shape how the industry incorporates human intelligence into the next generation of AI systems, with immediate access to a unique human data asset that positions you to make outsized impact.

What You’ll Be Doing

Strategic Leadership

  • Develop and execute Prolific's data science and applied AI strategy
  • Build and scale high-performing teams of data scientists and AI/ML engineers, with a strong culture of excellence, innovation, and impact
  • Partner directly with executive leadership to identify breakthrough opportunities where our human data advance AI capabilities
  • Create a technical vision that positions Prolific as the leader in human-centered AI development
  • Establish a technical culture that attracts and retains exceptional talent in a competitive market

Technical Direction

  • Lead the development of sophisticated ML/AI systems that enhance how human feedback is collected, validated, and utilized
  • Spearhead the creation of robust measurement frameworks and experimental designs to quantify our platform's capabilities and support emerging AI evaluation needs
  • Establish technical standards and best practices across data science and AI engineering
  • Balance technical innovation with operational excellence and business impact

Cross-Functional Impact

  • Translate technical capabilities into competitive advantages for the platform
  • Collaborate with platform engineering to create seamless integration paths for your team's innovations
  • Partner with research to rapidly operationalize promising approaches
  • Work with product teams to enhance platform capabilities through intelligent systems
  • Influence how the AI industry approaches human feedback through thought leadership

What You’ll Bring

  • 6+ years of experience in data science, AI/ML engineer, or related fields – preferably in leadership roles
  • Proven track record of building and scaling high-performing teams
  • Experience applying both traditional machine learning and modern AI techniques to solve real business problems
  • Strategic vision for how human data can fundamentally improve AI systems
  • Experience working with behavioral data, human feedback systems, or AI evaluation methodologies preferred – with interest in exploring innovative applications
  • Ability to work quickly in a fast paced challenging environment and deliver high quality results to stakeholders
  • Experience collaborating effectively with platform engineering and research teams
  • Demonstrated ability to balance innovation with practical delivery of robust, scalable systems
  • Exceptional communication skills with ability to influence at all levels of the organization
  • Strategic mindset with hands-on technical capabilities and a practical approach to problem-solving

Why Prolific is a great place to work

We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems.

We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breath and the best of humanity.

Working for us will place you at the forefront of AI innovation, providing access to our unique human data platform and opportunities for groundbreaking research. Join us to enjoy a competitive salary, benefits, and remote working within our impactful, mission-driven culture.

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.