We are a fast-growing HR tech startup backed by leading international VCs, having raised €9M+ from 360 Capital, IFF, Kfund, and 14Peaks. We are a team of 30+ professionals passionate about shaping the future of talent assessment. Skillvue is a Skill AI Assessment platform (SaaS) to hire top-skilled candidates and measure employee skill, culture, and leadership at scale to upskill and grow the workforce by leveraging AI. You will conduct research and validation workstreams across our assessment portfolio: defining competency frameworks, designing items and tasks, running data collection and analyses, and partnering with ML engineers to translate findings into production models and metrics. Own end-to-end research projects: literature review, research design, item/task development, pilot studies, full-scale data collection, and reporting. Develop and validate competency frameworks for soft and technical skills using factor analysis (CFA/EFA), IRT, classical test theory, and ML-based validation (e.G., Design scalable assessment tasks (situational judgment tests, simulations, work samples, micro-skills tasks) and automated scoring rubrics (including NLP and behavioral signal extraction). Run reliability, validity, fairness, and measurement invariance analyses across subgroups and contexts; Collaborate with peoplescientists and ML engineers to operationalize skill frameworks, AI models, create monitoring metrics (drift, fairness, validity), and integrate assessments into production pipelines. Build and maintain data collection protocols, consent/ethics procedures, and high-quality datasets suitable for psychometric and ML analyses. Master’s degree in organizational psychology, psychometrics or a closely related discipline (Ph.Strong track record in assessment research and psychometrics, including published work or equivalent evidence of applied research impact. Hands-on experience with CFA/EFA, IRT modeling, and classical test theory. Proficiency in statistical programming (R, Python, or both) and packages for psychometric analysis (lavaan, mirt, psych, lme4, or equivalents) and predictive modelling (e.G., random forest, neural networks, XAI) Fluency in English (C1) and strong written communication for technical and non-technical audiences. Team-oriented, proactive, and comfortable in an early-stage start-up with a flat hierarchy. NLP for free-text responses, computer vision, or multimodal feature extraction). Hand-on experience with GenAI, particularly Large Language Models (LLMs) Experience designing internationalized assessments and working with cross-cultural samples. Significant opportunity to shape product and research direction at an early-stage company. Remote work (within the EU timezone) Flexible, collaborative work environment and strong focus on scientific integrity.