Maki People
Science
AIScientist
Neural analysis suggests this role is
optimal for Mid+ candidates.
“AI Scientist at Maki People. Skills: AI model evaluation, psychometric validation, statistical analysis, LLMs, NLP, Python, R, BigQuery, fairness and bias analysis, predictive modelling. Assess the statistical accuracy and reliability of LLMs used for automated scoring. Evaluate and calibrate psychometric models to ensure scientific validity and comparability”
What You'll Achieve.
shaping the future of hiring through innovation, rigour, and collaboration; drives the development of high-quality content that sets our platform apart; ensure fairness, accuracy, and transparency; build reliable, valid, and impactful assessments; predict performance and potential with precision; optimize their workforce strategies; establish new standards in ethical AI use and hiring practices; driving exceptional outcomes for our clients; ensuring that Maki’s automated scoring systems are scientifically robust, fair, and continuously improving; ensure scientific validity and comparability across populations and test forms; ensure validity and alignment; maintaining model performance integrity; adhere to ethical and scientific standards; translate insights into actionable recommendations for clients and internal stakeholders; track model performance, drift, and stability over time
Industry & Context.
issue resolution; diagnostic analyses; evidence-based improvements
What They're Looking For.
Must Have
AI model evaluation, psychometric validation, statistical analysis, Python or R, cloud databases, ethical AI, data governance, compliance
Nice to Have
PhD, MSc, Computational Linguistics, Psychology, basic knowledge of psychometric modelling (e.g. , IRT, CFA, CAT), familiarity with LLMs and NLP techniques used for automated assessment and scoring, experience applying fairness and bias testing methodologies in AI-driven decisions, skilled in validation research ensuring reliability, construct validity, and practical relevance of assessments, experience with statistical software, experienced in collaborating across teams (engineering, product, content), communicating insights clearly to both scientific and business audiences, skilled in data visualisation, research writing, track record of publications or applied studies
What You'll Do.
Assess the statistical accuracy and reliability of LLMs used for automated scoring
Evaluate and calibrate psychometric models to ensure scientific validity and comparability
Test model robustness
Design research comparing AI-scored assessments with expert human judgments
Benchmark multiple LLMs
Develop hybrid scoring pipelines combining human oversight and AI-driven analytics
Detect and analyse potential biases in AI-generated or psychometric scores
Apply fairness and bias-mitigation techniques
Contribute to internal fairness dashboards and compliance documentation
Continuously evaluate model generalisability and fairness
Work with large-scale assessment and performance datasets to model relationships
Develop and test predictive models
Investigate anomalies raised by clients or internal QA
Conduct diagnostic analyses and recommend evidence-based improvements
Implement continuous monitoring systems
Explore prompt engineering
and model optimisation techniques
Translate technical findings into actionable insights for non-technical stakeholders
Contribute to internal and external research
How You'll Work.
Team & Collaboration
working closely with our COO; Collaborating with regulatory bodies and industry leaders; Equipping internal teams and clients with the knowledge and skills needed; Collaborate with data science, implementation and customer success teams; collaborating across teams (engineering, product, content)
Communication Scope
communicating insights clearly to both scientific and business audiences
Full Job Description
ABOUT THE SCIENCE TEAM At the heart of Maki People, the Science team is shaping the future of hiring through innovation, rigour, and collaboration. Led by our Head of Science, Aiden Loe, and working closely with our COO, Paul-Louis Caylar, this team drives the development of high-quality content that sets our platform apart. We don’t just create and validate assessments—we innovate. Our work spans: - Expanding a cutting-edge library of tests and tools. - Designing bespoke activities and experiences for clients. - Evaluating and refining AI-driven scoring algorithms and large language models (LLMs) to ensure fairness, accuracy, and transparency. - Leveraging psychometric expertise to build reliable, valid, and impactful assessments. - Developing tools that analyze candidate and job data to predict performance and potential with precision. - Supporting clients in using assessment data to optimize their workforce strategies, from talent acquisition to development and retention. - Leading original studies to explore emerging psychological and technological trends and sharing insights through publications, presentations, and client reports. - Collaborating with regulatory bodies and industry leaders to establish new standards in ethical AI use and hiring practices. - Equipping internal teams and clients with the knowledge and skills needed to understand and apply psychological and AI-driven insights effectively. As Maki continues to grow, the Science team is central to understanding user experiences, refining assessments, and driving broader adoption—all while upholding the highest scientific standards. Your impact as a AI Scientist will go beyond day-to-day responsibilities— you’ll be a key partner in shaping the future of recruitment while driving exceptional outcomes for our clients. ABOUT THE ROLE The AI Scientist works at the intersection of psychometrics, AI, and research, ensuring that Maki’s automated scoring systems are scientifically robust, fair, and continuou
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