Senior Applied Scientist Data Scientist

DeepRec.ai is partnering with a fast-growing London AI startup to hire a Senior Applied Scientist / Data Scientist. About the company Our client helps HR Tech vendors, staffing firms and employers prove and improve the fairness, accuracy and compliance of their AI hiring systems. They grew their customer base tenfold in 2025 and have already more than doubled ARR this year. Much of that growth comes from customers promoting them, because the company's audits help them win their own deals. The role You'll run highly defensible bias audits of high-stakes AI systems, used by everyone from startups to industry-leading enterprises. Regulators, courts, customers and candidates rely on these audits, so the methodology has to hold up. The work spans AI system evaluation, rigorous statistical analysis, synthetic data generation and hiring and selection science. You'll report to the CTO and work closely with the founders and product team. As one of a small number of data hires, you'll have real scope to shape the analytical function and your own role as the company grows. What you'll do

• Define the statistical tests, fairness metrics, sampling strategies and evaluation frameworks behind every audit
• Work with policy experts to turn regulation and emerging HR and AI standards into practical audit methodologies
• Build the datasets, test frameworks and workflows that make audits consistent, efficient and high quality
• Interpret results with care for uncertainty and limitations, and shape how findings are presented in reports and dashboards
• Bring technical authority to high-stakes conversations with customers' data science, legal and compliance teams
• Write the explanations, white papers and industry reports that let outside experts scrutinise and trust the approach What you'll bring
• 6+ years of applied statistics or data science in a commercial, high-performing product organisation
• Hands-on fluency in confidence intervals, hypothesis testing, power analysis, experimental design, causal inference and Bayesian modelling
• Experience designing evaluation methodologies, including black-box and counterfactual approaches, and the test datasets behind them
• Practical familiarity with evaluating classic ML models, LLM-based systems and AI agents, including their failure modes
• Strong Python for statistical analysis and reproducible evaluation workflows
• Comfort bringing structure to open-ended problems, and clear communication with technical and non-technical audiences Nice to have
• Background in HR analytics, I/O psychology or psychometrics (e.g. adverse impact analysis)
• Familiarity with AI and hiring regulation
• Experience with explainability for black-box system What's on offer
• Meaningful equity in a fast-growing business
• Private health insurance
• 33 days holiday (including bank holidays)
• Hybrid working, 3 days a week in the London office
• £500 annual learning and development budget Interview process Initial screen, then founder interviews with the CEO and CTO, a short take-home case study (2–3 hours), an on-site case review, and finally references and offer.