Senior Research Scientist, AI & Workforce Intelligence

🕒 June 10

🇺🇸 United States – Remote

💵 $130k - $150k / year

⏰ Full Time

🟠 Senior

🧠 AI Research Scientist

👻 Ghost score 18%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Wonderlic

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 1937

👥 HR Tech

🏢 Enterprise

HR Tech • Enterprise

Wonderlic is a company that provides pre-hire assessment and employee development tools designed to help businesses improve talent decisions across the entire employee journey. Their products, Wonderlic Select and Wonderlic Develop, offer predictive insights into cognitive ability, personality, and motivation, helping organizations make informed hiring decisions and boosting employee development. Wonderlic's platform is intuitive and scalable, aiming to eliminate bias and promote fairness in hiring and development processes. By providing role-specific, personalized results, Wonderlic supports HR teams, managers, employees, and candidates in achieving and identifying potential and excellence within workplace environments.

📋 Description

• Own the architecture, integrity, and continuous expansion of Wonderlic’s AI job analysis system • Ingest and analyze labor market data from O*NET, LinkedIn, Indeed, and other sources • Build and refine models that infer work content from unstructured text • Extrapolate cognitive complexity ratings, norm groups, and occupational interest profiles for thousands of jobs • 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, adverse impact considerations, norm group construction, and evidence-based evaluation standards • Ensure AI products meet professional and legal standards for selection and development tools • Establish a roadmap for continued AI integration into the platform • Develop new assessments using emerging technologies for richer and more secure evaluation

🎯 Requirements

• 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 both 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, 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 • Ability to own ambiguous, high-complexity problems • Familiarity with occupational taxonomies, vocational interests, or cognitive ability frameworks is a plus

🏖️ Benefits

• Work from anywhere in the United States • Four-day work week • Generous PTO • Paid company shutdown from 12/24 to 1/1 • Medical insurance • Dental insurance • Vision insurance • 401(k) with matching • Paid new parent leave