At a Glance
- Tasks: Define analytical standards for evaluating high-stakes AI systems and ensure fairness and accuracy.
- Company: Join Warden AI, a pioneering company focused on responsible AI adoption.
- Benefits: Enjoy 33 days holiday, hybrid working, and a ÂŁ500 learning budget.
- Why this job: Shape the future of AI assurance and make a real impact in a fast-growing field.
- Qualifications: 5+ years experience in AI bias, HR analytics, or rigorous statistical analysis.
- Other info: Collaborative environment with opportunities for personal and professional growth.
The predicted salary is between 36000 - 60000 ÂŁ per year.
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 fastâgrowing platforms and global enterprises to enable the responsible adoption of AI worldwide.
About the role: We are hiring a Senior Data Scientist to define the analytical standards that underpin our evaluation of highâstakes 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 handsâon 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 standardâsetter 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 youâll do:
- 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 HR and AI standards 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 highâquality audits.
- Take a longâterm, strategic view. Identify emerging risks, opportunities, regulatory shifts, and industry developments, and help define how our AI assurance approach should evolve over the next 12â24 months.
- Guide the evolution of our longâterm 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 highâstakes 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 white papers or blog posts to help build trust in our work.
What you should bring:
- Relevant academic or equivalent background with a strong, professional seniorâlevel track record over 5+ years and deep expertise in at least two of the following areas:
- AI bias and responsible AI, including fairness evaluation, model assessment, or the design of responsibleâAI practices in applied settings.
- HR analytics or IâO psychology, with experience in selection processes, adverse impact analysis, validity considerations, or defensible evaluation practices.
- Statistically rigorous analytical work in regulated or highâstakes environments, with fluency in statistical reasoning, demonstrated through defensible, reproducible analysis.
- Fluency in Python for analytical work. Youâre 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 expertâlevel competence across all parts of the role.
- Comfortable with both depth and ambiguity. You enjoy tackling openâended 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 highâagency. You like working closely with founders, engineers, and customers, and you move work forward even when information is incomplete.
- Contextâaware 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 youâre excited by the chance to help shape how AI assurance is done as the field matures.
This role isnât for you if...
- You prefer narrow, wellâscoped analytical problems. The work spans statistics, regulation, HR practice, product, and customer context.
- You need complete information before acting. Many decisions rely on judgment under uncertainty and evolving guidance.
- You donât enjoy creating structure from ambiguity. Youâll help shape frameworks, workflows, and evaluation patterns as we grow.
- Youâd rather follow established methods. This role involves defining and refining our evaluation process for AI systems.
- Youâre uncomfortable owning the quality bar. Youâll often be the one deciding if an analysis is defensible enough to publish.
- You prefer to stay behind the scenes. Youâll join highâstakes 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 publicâfacing 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 ÂŁ500 per year
Our interview process involves the following stages:
- Initial screen (40min) â Intro call with our CTO to align on your background and the role.
- Founder screen (40min + 40min) â Conversation with our CEO about values, how you collaborate in a highâagency, fastâmoving 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, highâstakes evaluations, and your clarity of communication.
- Takeâhome task â Short analytical case study that reflects the kind of realâworld evaluation challenges we face and sets the stage for the onâsite case review.
- Onâsite interview (80min) â A collaborative case review and a conversation about the strategic impact you could have on Warden over the next 12â24 months.
- Reference checks & Offer â We move quickly from references to a clear offer.
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.
Weâre an equalâopportunity 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.
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 hiring@wardenâai.com.
Senior Data Scientist in London employer: Warden AI
Contact Detail:
Warden AI Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land Senior Data Scientist in London
â¨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Warden AI. A friendly chat can go a long way in getting your foot in the door.
â¨Tip Number 2
Prepare for the interview by brushing up on your analytical skills and understanding of AI bias. Show us you know your stuff and can tackle high-stakes evaluations with confidence!
â¨Tip Number 3
Donât just talk about your experience; bring it to life! Use real examples from your past work to demonstrate how youâve tackled similar challenges and made an impact.
â¨Tip Number 4
Apply through our website! Itâs the best way to ensure your application gets seen. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace Senior Data Scientist in London
Some tips for your application đŤĄ
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience in AI bias, statistical analysis, and HR practices. We want to see how your skills align with our mission at Warden AI!
Showcase Your Analytical Skills: In your application, donât just list your qualificationsâgive us examples of how you've tackled complex analytical problems. We love seeing how youâve turned ambiguity into structured solutions!
Communicate Clearly: Remember, clarity is key! Use straightforward language to explain your past projects and methodologies. We appreciate candidates who can break down complex ideas for different audiences.
Apply Through Our Website: We encourage you to apply directly through our website. Itâs the best way for us to receive your application and ensures youâre considered for this exciting opportunity at Warden AI!
How to prepare for a job interview at Warden AI
â¨Know Your Stuff
Make sure you brush up on your knowledge of AI bias, fairness evaluation, and statistical analysis. Be ready to discuss how these concepts apply to real-world scenarios, especially in high-stakes environments. This will show that youâre not just familiar with the theory but can also translate it into practice.
â¨Prepare for the Case Study
The take-home task is a big part of the interview process, so treat it seriously! Familiarise yourself with the types of analytical challenges Warden AI faces. Practice structuring your analysis clearly and concisely, as this will be crucial during the on-site case review.
â¨Communicate Clearly
Youâll need to explain complex ideas simply, so practice articulating your thoughts. Think about how you can adapt your message for different audiences, whether theyâre technical or non-technical. Clear communication will help you build trust and credibility with stakeholders.
â¨Show Your Strategic Thinking
Warden AI is looking for someone who can take a long-term view. Be prepared to discuss how you would identify emerging risks and opportunities in the AI landscape. Think about how your analytical work can evolve alongside regulatory shifts and industry developments.