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Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in AI job analysis systems, applying I-O psychology principles, and leveraging modern NLP and ML engineering techniques to produce scientifically defensible assessments. Capable of integrating occupational taxonomies and ensuring compliance with legal and ethical standards in employment contexts.
Highest-signal resume keywords
Graduate Degree In I-O PsychologyML Engineering ExperienceApplied NLP SkillsOccupational Data Modeling KnowledgeResponsible AI Judgment
About the role
Key responsibilities & impact- 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
Requirements
What you’ll need- 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
Benefits
Comp & perks- 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
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine Learning EngineeringNatural Language ProcessingText ClassificationModel TuningSemantic SearchClusteringTransformer ArchitecturesGenerative AI EvaluationError AnalysisRegression Testing
Soft Skills
Problem SolvingCollaborationCommunication
Industry Keywords
O*NETESCOI-O PsychologyAssessment InterpretationAdverse ImpactNorm Group ConstructionEvidence-Based EvaluationAlgorithmic FairnessVocational InterestsCognitive Ability Frameworks