Senior Research Scientist, AI & Workforce Intelligence

🕒 il y a 14 jours

🇺🇸 États-Unis – Télétravail

💵 $130 000 - $150 000 / an

⏰ Temps Plein

🟠 Senior

🧠 Chercheur en IA

👻 Score fantôme 0%

Ce que ça veut dire : la probabilité que personne ne recrute vraiment pour cette offre.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

Postuler Maintenant

Trouver des Emplois à Distance Similaires

Wonderlic

Site WebLinkedInTous les Emplois

51 - 200 employés

Fondée en 1937

👥 RH Tech

🏢 Entreprise

HR Tech • Enterprise

Wonderlic est une société qui fournit des outils d'évaluation pré-embauche et de développement des employés conçus pour aider les entreprises à améliorer les décisions relatives aux talents tout au long du parcours des collaborateurs. Leurs produits, Wonderlic Select et Wonderlic Develop, offrent des informations prédictives sur les capacités cognitives, la personnalité et la motivation, aidant les organisations à prendre des décisions d'embauche éclairées et à renforcer le développement des employés. La plateforme de Wonderlic est intuitive et évolutive, visant à éliminer les biais et à promouvoir l'équité dans les processus de recrutement et de développement. En fournissant des résultats personnalisés et spécifiques au rôle, Wonderlic soutient les équipes RH, les managers, les employés et les candidats dans l'accomplissement et l'identification du potentiel et de l'excellence au sein des environnements professionnels.

Description

• Own the architecture, integrity, and continuous expansion of Wonderlic’s AI job analysis system • Ingest labor market data from O*NET, LinkedIn, Indeed, and other sources to produce job analysis at scale • Build and refine models that infer work content from unstructured text • Leverage and expand occupational taxonomies such as O*NET and ESCO • Ensure system outputs are scientifically defensible and scalable as work evolves • Partner with product managers, engineers, and I-O psychologists to translate scientific requirements into AI-powered systems • Advise on AI approaches for assessment interpretation, manager and team reporting, and coaching content • Serve as an internal resource on ML and AI capabilities and limitations in assessment and organizational contexts • Contribute to Wonderlic’s external scientific credibility • Apply I-O psychology principles, including adverse impact consideration, norm group construction, and evidence-based evaluation standards • Ensure AI products meet professional and legal standards for selection and development tools • Establish relationships with I-O and Product teams and create a roadmap for AI integration • Expand the Jobs Engine’s reach, accuracy, coverage, and quality of inferences • Help develop new assessments using emerging technologies for richer and more secure evaluation

🎯 Exigences

• Graduate degree in I-O Psychology, Organizational Psychology, Organizational Development, or closely related field; quantitative focus strongly preferred • Demonstrated ML engineering experience with shipped, production-grade systems, not just research or coursework • Experience applying modern NLP methods to behavioral, assessment-based, or labor market data • Track record of work that was technically sound and legally/professionally defensible • Minimum 3 years of applied industry experience • Applied NLP and ML engineering skills, including embeddings, semantic search, clustering, text classification, transformer architectures, model tuning, and evaluation • Occupational data modeling knowledge, including job titles, task statements, skills, competencies, credentials, job families, seniority levels, title normalization, job similarity, role differentiation, O*NET, and ESCO • Responsible AI judgment in employment contexts, including fairness, explainability, auditability, bias mitigation, human review, and legal and ethical considerations • Generative AI evaluation skills, including rubric-based review, groundedness checks, error analysis, regression testing, and LLM output evaluation • Product judgment for applied ML systems • Working fluency with assessment and I/O concepts, including job relatedness, criterion relationships, adverse impact, norm groups, assessment profiles, and score interpretation • Ability to own ambiguous, high-complexity problems • Experience at the intersection of I-O science and algorithmic fairness strongly preferred • Familiarity with occupational taxonomies, vocational interests, or cognitive ability frameworks a significant plus

🏖️ Avantages

• Full-time, 32-hour workweek across four days • Generous PTO • Paid holidays • Paid company shutdown from December 24 through January 1 • Medical coverage • Dental coverage • Vision coverage • 401(k) with company matching • 10 weeks of paid new parent leave • Dedicated wellness benefit • Remote work from anywhere in the United States

📊 Vérifiez votre score de CV pour ce poste

Améliorez vos chances d'obtenir un entretien en vérifiant votre score de CV avant de postuler.

Télécharger le CV