Head of Data Science & Applied AI New Remote, UK...

Prolific
uk
5 days ago
Create job alert

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

Related Jobs

View all jobs

Construction Logistics Leads x 3

Head of Data Science | London Market

Head of Data Science

Head of Data Science

Head Of Data Science

Head Of Data Science And Ai

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Top 10 Best UK Universities for Data Science Degrees (2025 Guide)

Discover ten of the strongest UK universities for Data Science degrees in 2025. Compare entry requirements, course content, research strength and industry links to choose the right programme for you. Data is the currency of the modern economy, and professionals who can wrangle, model and interpret vast datasets are in demand across every sector—from biotechnology and finance to sport and public policy. UK universities have been at the forefront of statistics, artificial intelligence and large-scale computing for decades, making the country a prime destination for aspiring data scientists. Below, we profile ten institutions whose undergraduate or postgraduate pathways excel in data science. Although league tables vary each year, these universities have a proven record of excellence in teaching, research and industry collaboration.

Veterans in Data Science: A Military‑to‑Civilian Pathway into Analytical Careers

Introduction The UK Government’s National AI Strategy projects that data‑driven innovation could add £630 billion to the economy by 2035. Employers across healthcare, defence, and fintech are scrambling for professionals who can turn raw data into actionable insights. In 2024 alone, job‑tracker Adzuna recorded a 42 % year‑on‑year rise in data‑science vacancies, with average advertised salaries surpassing £65k. For veterans, that talent drought is a golden opportunity. Whether you plotted artillery trajectories, decrypted enemy comms, or managed aircraft engine logs, you have already practised the fundamentals of hypothesis‑driven analysis and statistical rigour. This guide explains how to translate your military experience into civilian data‑science language, leverage Ministry of Defence (MoD) transition programmes, and land a rewarding role building predictive models that solve real‑world problems. Quick Win: Take a peek at our live Junior Data Scientist roles to see who’s hiring this week.

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.