About Warden AI
AI is being deployed across every industry, transforming how decisions are made and how people interact with technology. But as adoption accelerates, so do concerns about bias, accuracy, and accountability. Warden AI safeguards this transformation by making sure AI systems are fair, transparent, accurate, and explainable.
Founded in 2023 and backed by investors from Playfair, Monzo, Onfido, and Codat, our platform continuously audits AI models, delivering independent oversight through dashboards, reports, and certifications. With teams in London and Austin, we partner with both fast-growing platforms and global enterprises to enable the responsible adoption of AI worldwide.
Read why Playfair Capital invested in Warden AI.
About the role
We are hiring a Senior Data Scientist to define the analytical standards that underpin how we evaluate high-stakes AI systems. The role spans fairness evaluation, rigorous statistical analysis, and an applied understanding of hiring and selection procedures. Most candidates will start strongest in one of these areas and develop depth across all three, enabling you to influence everything from how we design tests and interpret results to how we guide customers, shape product decisions, and meet the expectations of an evolving responsible AI landscape.
You will report to the CTO and work closely with the founders and product team across hands-on analysis, methodological design, and strategic thinking. Your work will elevate our analytical standards, strengthen the confidence customers place in us, and play a central role in establishing Warden as the standard-setter for rigorous, defensible evaluations.
As one of our early data hires, you will have high agency to shape both how our analytical function evolves and the scope of your own role as we grow.
What you’ll do
Here are a few examples of things you might be working on:
- Set and uphold rigorous analytical methodology. Define the statistical tests, fairness metrics, sampling strategies, and evaluation frameworks we rely on, and embed the checks and validation patterns that keep our analytical work accurate, reproducible, and defensible.
- Translate regulations and standards into practical tests. Turn legal requirements, guidance, and emerging standards in HR and AI into clear, defensible audit procedures and criteria.
- Design the foundations for audit execution. Create the datasets, test frameworks, workflows, and analysis patterns that enable consistent, efficient, and high-quality audits.
- Take a long-term, strategic view. Identify emerging risks, opportunities, regulatory shifts, and industry developments, and help define how our approach to AI assurance needs to evolve over the next 12–24 months.
- Guide the evolution of our long-term data capabilities. Anticipate the data assets and analytical foundations we will need as our product expands and the regulatory landscape evolves.
- Define how we analyze and interpret results. Establish the principles, evidence thresholds, and approaches for handling uncertainty and limitations, and help the team communicate findings clearly and consistently.
- Support key high-stakes conversations. Bring technical authority on data, methodology, and context to stakeholder discussions and help address detailed questions with confidence.
- Contribute to documentation and external credibility. Write accessible explanations of our approach and contribute to whitepapers or blog posts that help build trust in our work.
What you should bring
- Strong, senior-level track record over 5+ years and deep expertise in at least one of the following areas:
- AI bias and responsible AI, including fairness evaluation, model assessment, or the design of responsible-AI practices in applied settings.
- HR analytics or I-O psychology, with experience in selection processes, adverse impact analysis, validity considerations, or defensible evaluation practices.
- Statistically rigorous analytical work in regulated or high-stakes environments, with fluency in statistical reasoning and the ability to produce defensible, reproducible analysis.
- Fluency in Python for analytical work. You’re comfortable using Python for statistical analysis, data preparation, and reproducible evaluation workflows.
- Grow expertise across domains. You take ownership of your development and quickly build expert-level competence across all parts of the role.
- Comfortable with both depth and ambiguity. You enjoy tackling open-ended analytical problems, reasoning through uncertainty, and bringing structure where none exists.
- Thoughtful and rigorous. You care about evidence, clarity, and defensibility, and you take pride in producing analysis that stands up to scrutiny.
- A clear and responsible communicator. You can explain complex ideas simply, adapt your message for different audiences, and help others make informed decisions.
- Collaborative and high-agency. You like working closely with founders, engineers, and customers, and you move work forward even when information is incomplete.
- Context-aware and able to connect dots. You track how regulation, standards, customer needs, and industry expectations evolve, and use that context to inform decisions and shape direction.
- Motivated by impact. You want your work to matter, and you’re excited by the chance to help shape how AI assurance is done as the field matures.
This role isn’t for you if…
- You prefer narrow, well-scoped analytical problems. The work spans statistics, regulation, HR practice, product, and customer context.
- You need complete information before acting. Many decisions rely on judgement under uncertainty and evolving guidance.
- You don’t enjoy creating structure from ambiguity. You’ll help shape frameworks, workflows, and evaluation patterns as we grow.
- You’d rather follow established methods. This role involves defining and refining how we evaluate AI systems.
- You’re uncomfortable owning the quality bar. You’ll often be the one deciding if an analysis is defensible enough to publish.
- You prefer to stay behind the scenes. You’ll join high-stakes customer conversations where clarity and judgement matter.
- You avoid work that blends analysis with explanation. Turning complex results into clear, responsible guidance is core to the job.
- You prefer to avoid external scrutiny. The role involves sharing our work with enterprise stakeholders and the wider ecosystem, and contributing to public-facing materials to build trust and credibility.
What we offer:
- 33 days holiday (incl. bank holidays)
- Hybrid working model (we spend 3 days/week in our London office)
- Learning and Development budget of £500 per year
Interview process
Our interview process involves the following stages:
- Initial screen (40min) - Intro call with our CTO to align on your background and the role.
- Founder screen (40min + 40min)
- Conversation with our CEO about values, how you collaborate in a high-agency, fast-moving environment, and how you turn expertise into customer and market trust.
- Conversation with our CTO/Data about your analytical judgement, how you identify what really matters in ambiguous, high-stakes evaluations, and your clarity of communication.
- Take-home task - Short analytical case study that reflects the kind of real-world evaluation challenges we face and sets the stage for the on-site case review.
- On-site interview (80min) - A collaborative case review and a conversation about the strategic impact you could have on Warden over the next 12–24 months.
- Reference checks & Offer - We move quickly from references to a clear offer.
Our average process takes around 2-3 weeks, but we will always work around your availability.
If you have any specific questions or want to talk through reasonable adjustments ahead of or during the application, please contact us at any point at .
Equal opportunities for everyone
Diversity and inclusion are a priority for us, and we are making sure we have lots of support for all of our people to grow at Warden AI. We embrace diversity in all of its forms and create an inclusive environment for all people to do the best work of their lives with us. This is integral to our mission of supporting the responsible adoption of AI systems.
We’re an equal-opportunity employer. All applicants will be considered for employment without attention to ethnicity, religion, sexual orientation, gender identity, family or parental status, national origin, veteran status, neurodiversity status or disability status.
