4 часа назад
AI Scientist
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Scientist (AI, Psychometrics): Evaluating and improving AI-driven scoring systems and psychometric assessments with an accent on model validity, fairness, robustness, and predictive performance. Focus on benchmarking LLMs, building hybrid human-AI scoring pipelines, detecting bias, and monitoring model drift across assessment and performance datasets.
Location: Hybrid in Paris or London
Company
develops a hiring platform focused on assessments, automated scoring, and workforce insights.
What you will do
- Evaluate the statistical accuracy, reliability, robustness, and fairness of LLM-based automated scoring systems.
- Calibrate psychometric models such as CTT, IRT, CFA, and CAT across populations and assessment forms.
- Benchmark closed- and open-source LLMs and build hybrid scoring pipelines combining human oversight with AI analytics.
- Design validation research comparing AI-scored assessments with expert judgments and model relationships between assessment results, job performance, and retention.
- Develop fairness dashboards, compliance documentation, and continuous monitoring for model performance, drift, and stability.
- Translate research findings into recommendations for data science, implementation, customer success, clients, and other stakeholders.
Requirements
- Advanced degree (PhD or MSc) in Data Science, Machine Learning, Psychometrics, Computational Linguistics, or Psychology.
- Expertise in AI model evaluation, psychometric validation, statistical analysis, and reliability and construct-validity research.
- Familiarity with LLMs, NLP techniques, automated assessment, fairness testing, bias mitigation, ethical AI, data governance, and compliance.
- Proficiency in Python or R, statistical software, and cloud databases such as BigQuery.
- Experience with data visualisation, research writing, publications, or applied studies.
- Ability to collaborate across engineering, product, and content teams and communicate with scientific and business audiences.
Culture & Benefits
- Opportunity to shape the Science team and the product as an early employee.
- Work focuses on scientific rigour, ethical AI, transparent model governance, and collaboration.
- Research insights may be shared through reports, publications, presentations, and conferences.
Hiring process
- Screening assessment lasting 20 minutes.
- Hiring manager, executive, technical deep-dive, and co-founder interviews.
- Power skill assessment with an AI agent.
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