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: Make a real impact in shaping the future of AI assurance and transparency.
- Qualifications: 5+ years in data science with expertise in AI bias, HR analytics, or statistical analysis.
- Other info: Collaborative environment with opportunities for personal and professional growth.
The predicted salary is between 36000 - 60000 ÂŁ per year.
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.
About the role
We are hiring a Senior Data Scientist to define the analytical standards that underpin our evaluation of 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
- 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 high‑quality audits.
- Take a long‑term, strategic view. Identify emerging risks, opportunities, regulatory shifts, and industry developments, and help define how our AI assurance approach should 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 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 senior‑level 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 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, demonstrated through defensible, reproducible analysis.
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 judgment 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 our evaluation process for 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 matters.
- 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 ÂŁ500 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.
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@warden-ai.com.
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.
Senior Data Scientist employer: Warden AI Ltd.
Contact Detail:
Warden AI Ltd. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with Warden AI folks on LinkedIn. Building relationships can open doors that applications alone can't.
✨Tip Number 2
Prepare for those interviews! Research Warden AI's mission and values, and think about how your skills align with their goals. Practise answering common data science questions and be ready to discuss your past projects.
✨Tip Number 3
Show off your analytical chops! Bring examples of your work to the interview, whether it's a project or a case study. Demonstrating your thought process and problem-solving skills can really impress the team.
✨Tip Number 4
Don’t forget to follow up! After your interview, send a thank-you note expressing your appreciation for the opportunity. It’s a nice touch that keeps you fresh in their minds and shows your enthusiasm for the role.
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience in AI bias, statistical analysis, or HR analytics. We want to see how your skills align with the role of Senior Data Scientist at Warden AI!
Showcase Your Analytical Skills: In your application, don’t shy away from sharing specific examples of your analytical work. Whether it’s a project where you tackled high-stakes evaluations or developed rigorous methodologies, we love seeing your thought process in action.
Communicate Clearly: Remember, clarity is key! When explaining your past experiences or methodologies, keep it simple and straightforward. We appreciate candidates who can break down complex ideas into digestible bits.
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Warden AI Ltd.
✨Know Your Stuff
Make sure you brush up on your knowledge of AI bias, fairness evaluation, and statistical analysis. Warden AI is looking for someone who can define analytical standards, so be prepared to discuss your experience in these areas and how you've applied them in real-world scenarios.
✨Show Your Strategic Thinking
This role requires a long-term view on data capabilities and regulatory shifts. Think about how you can contribute to Warden's evolution over the next 12–24 months. Be ready to share your insights on emerging risks and opportunities in the AI landscape during the interview.
✨Communicate Clearly
Warden values clear communication, especially when explaining complex ideas. Practice articulating your thoughts simply and effectively. You might be asked to explain your analytical processes or findings, so make sure you can break them down for different audiences.
✨Be Collaborative
As a Senior Data Scientist, you'll work closely with founders, engineers, and customers. Highlight your collaborative experiences and how you've moved projects forward in ambiguous situations. Show that you're comfortable taking ownership and driving results even when information is incomplete.