{"id":1759510,"url":"https://alion.io/job/wonderlic-senior-research-scientist-ai-workforce-intelligence","title":"Senior Research Scientist, AI & Workforce Intelligence","company":{"id":2776658,"name":"Wonderlic","domain":"wonderlic.com","url":"https://alion.io/company/wonderlic","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"JazzHR","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":130000,"max":150000,"currency":"USD","period":"year","gross":null,"usd_annual":150000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Embeddings","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false}],"status":"live","first_seen_at":"2026-10-03T10:20:44Z","employer_posted_date":null,"last_verified_at":"2026-10-03T10:20:44Z","board_verified":false,"closed_at":null,"days_open":16,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":16},"description":"About Us\nWork a four-day week from anywhere for a company where people genuinely believe in what they do. Wonderlic leads the way in fair, predictive science to create a world where everyone finds and thrives in their best job—and that starts with you. We expertly combine our science-based assessment expertise with I-O psychology, machine learning, and artificial intelligence to deliver evidence-based insights that empower smarter employment decisions. Our simple, intuitive assessment tools help sophisticated HR teams identify top applicants, predict on-the-job performance, and ensure our own team is engaged and equipped to do their best work.\n\nWonderlic has always championed progressive, sustainable approaches that allow people to excel professionally while living balanced, fulfilling lives.Here are some of the ways we do that: \n\nWork from anywhere in the United States \n\nFour-day work week\n\nGenerous PTO plus a paid company shutdown from 12/24 to 1/1\n\nBenefits include medical, dental, vision, 401k with matching, paid new parent leave\n\nWhat Sets Us Apart:\n\nScientific Precision: We apply rigorous scientific methodologies to develop assessments that accurately gauge individuals' potential and fit within various organizational contexts.\n\nInnovation: Our dedication to continuous improvement drives us to explore cutting-edge techniques and technologies, ensuring our assessments remain at the forefront of talent assessment.\n\nImpactful Solutions: By integrating I-O Psychology principles into our processes, we deliver solutions that not only meet the immediate hiring needs of organizations but also contribute to long-term success and retention.\n\nOverview:Wonderlic is seeking a Senior Research Scientist to sit at the precise intersection of I-O psychology and machine learning - someone who has spent time building real systems with real data who cares deeply about what those systems are predicting. This is not a role for an ML engineer who finds people data interesting as a side project, or for an I-O psychologist who has learned to code. We’re looking for someone who has genuinely lived in both worlds and is ready to own the problems that live between them.\nWonderlic built its applied AI/ML team from scratch, developed the Jobs Engine, a first-of-its-kind machine learning system for job analysis at scale, and won the 2025 SIOP Machine Learning Competition. We’re now refining and expanding that work to deliver sharper, richer job analysis insights across thousands of roles. You will own the continued improvement of our jobs engine, the system that ingests labor market data and produces job analysis at scale across thousands of roles, and serve as one of the organization’s experts on how AI should be applied to both employee selection and development.\nYour Impact:As Senior Research Scientist, you will set the scientific and technical direction for how Wonderlic understands work at scale and translates assessment science into AI-powered insight. Your work will directly determine the quality, defensibility, and reach of the inferences our platform makes about jobs and people - inferences that drive hiring decisions, development plans, and coaching conversations for millions of users. You will be the person in the organization who can hold both the I-O science question and the production ML question in the same breath, and answer both.\nWhat You’ll DoLead the Continued Development of the Jobs Engine: Own the architecture, integrity, and continuous expansion of Wonderlic’s AI job analysis system, which ingests labor market data from O*NET, LinkedIn, Indeed, and other sources to extrapolate cognitive complexity ratings, norm groups, and occupational interest profiles for thousands of jobs. Build and refine the models that make inferences about work content from unstructured text. Leverage existing occupational taxonomies (e.g., O*NET, ESCO) where appropriate but also expand beyond them. Ensure all outputs are scientifically defensible and scalable as the nature of work evolves.\nAct as an Expert on AI Implementation Across the Organization: Partner with product managers, engineers, and I-O psychologists to translate scientific requirements into AI-powered systems and ensure those systems meet the standards the work demands. Advise on which approaches are best suited to specific implementation challenges - assessment interpretation, manager and teams reporting, coaching content - and help teams understand what good looks like before they build and after they ship. Serve as an internal resource on what ML and AI can and cannot do in assessment and organizational contexts, and contribute to Wonderlic’s external scientific credibility.\nDrive Scientific Rigor: Apply I-O psychology principles - adverse impact consideration, norm group construction, and evidence-based evaluation standards - to every system you build. Ensure that Wonderlic’s AI products meet professional and legal standards for selection and development tools. Push back when speed is being prioritized at the expense of defensibility, and find pragmatic paths forward when theoretical purity would prevent shipping.\nWhat Success Looks Like: In your first six months, you will have a deep understanding of the jobs engine architecture and shipped at least one meaningful improvement to its coverage, accuracy, or scientific defensibility. You will have established working\nrelationships with the I-O and Product teams and have a clear roadmap for the continued integration of AI into the platform. \nWithin a year, you will have materially expanded the jobs engine’s reach and accuracy with demonstrable improvements to its coverage and the quality of inferences it produces. You will have contributed to the continued integration of AI across the platform, and be the person your colleagues go to with the hardest ML-meets-IO-science problems - not because you have every answer, but because you know how to find them.\nThe long-term marker of success is a jobs engine that provides defensible, scaled job analysis inference across millions of roles using a wide variety of inputs, AI capabilities integrated into the platform in ways that hold up to scientific and professional scrutiny, and a track record of using these technologies to improve people’s understanding of themselves, their work, and their teams. You will also have helped to develop new assessments that leverage emerging technologies which allow for richer and more secure evaluation of individuals.\nWhat We’re Looking For: Skills & Capabilities:\n\nApplied NLP and ML engineering skills: embeddings, semantic search, clustering, text classification, transformer architectures, model tuning and evaluation, all on potentially messy, unstructured data\n\nOccupational data modeling: job titles, task statements, skills, competencies, credentials, job families, seniority levels, title normalization, job similarity, role differentiation, and occupational frameworks such as O*NET and ESCO\n\nResponsible AI judgment in employment contexts: fairness, explainability, auditability, bias mitigation, human review, and legal and ethical considerations in AI-supported selection and employee development systems\n\nGenerative AI evaluation skills: rubric-based review, groundedness checks, error analysis, regression testing, and evaluation of LLM-generated job descriptions, work-context summaries, and assessment result contextualization.\n\nProduct judgment for applied ML systems: balancing accuracy, explainability, automation, expert review, user input, maintainability, uncertainty, and job-specific nuance.\n\nWorking fluency with assessment and I/O concepts: job relatedness, criterion relationships, adverse impact, norm groups, assessment profiles, and score interpretation.\n\nAbility to own ambiguous, high-complexity problems: framing underspecified problems, challenging weak assumptions, learning domain constraints quickly, and driving durable solutions in a small-company environment.\n\nMindset:\nYou came to I-O psychology because you care about work - what makes it meaningful, who thrives in it, how to measure fit. That hasn’t changed.\n\nYou have a healthy relationship with “good enough”: you know that perfect is the enemy of shipped, and you have the judgment to know where the line is.\n\nYou can hold both worlds simultaneously: what does this score mean for a real person, and how do I build the system that generates it.\n\nYou are genuinely curious about the problems that exist for both employee selection and development, not just tolerant of them.\n\nYou thrive in an environment that requires creativity and scrappiness: you can work comfortably in a situation where the problems are hard, the team is small, the constraints are many, and the ownership is real.\n\nQualifications\nGraduate degree in I-O Psychology, Organizational Psychology, Organizational Development, or closely related field (quantitative focus strongly preferred); doctoral degree a plus\n\nDemonstrated ML engineering experience with shipped, production-grade systems - not just research or coursework\n\nExperience applying modern NLP methods to behavioral, assessment-based, or labor market data \n\nTrack record of work that had to be both technically sound and legally/professionally defensible\n\nMinimum 3 years of applied industry experience; 5+ years preferred\n\nExperience at the intersection of I-O science and algorithmic fairness strongly preferred\n\nFamiliarity with occupational taxonomies, vocational interests, or cognitive ability frameworks a significant plus\n\nCompensation:$130,000 to $150,000 based on experience and expertise.\n\nOur Policy\nAffirmative Action Plan/Equal Employer Opportunity (AAP/EEO) Statement: Research suggests that both the confidence gap and imposter syndrome can make members of some groups (including women, members of the LGBTQIA+ and BIPOC communities, and candidates of less traditional age, education, or background) less likely to apply for jobs when they don’t meet 100% of the qualifications. At Wonderlic, we are in the business of identifying potential, and we encourage all interested candidates to apply. \n\nWonderlic is proud to be an equal employment opportunity/affirmative action employer. Here, diversity is valued and celebrated, and this is what makes us such a successful team. Wonderlic does not discriminate in employment on the basis of race, color, religion, gender, gender identity, pregnancy status, national origin, sexual orientation, marital status, disability, genetic information, age, parental status, military/veteran status, or any other factor protected by law. \n\nIn addition, we will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive other benefits and privileges of employment. Please get in touch with us at  to request an accommodation.\n\nDisclaimer: This job description is not designed to include a comprehensive list of duties and responsibilities that are required of the employee. Duties and responsibilities may change or be assigned at any time, with or without notice.\n\n#BI-Remote \nOriginally posted on Himalayas","description_format":"text","description_chars":11200,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["401k plan"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Education","Skill Assessment"],"lifecycle":[{"event":"open","at":"2026-10-03T12:11:24Z"}],"visa":[],"liveness":{"score":63,"band":"ok","label":"Likely open","p_open":0.85,"p_active":0.824,"p_room":0.9,"age_days":15,"expected_fill_days":39,"reasons":["seen:15","win:mid"],"computed_at":"2026-10-19T05:45:15Z"},"pay":{"stated_usd_annual":150000,"is_top_pay":false},"html_url":"https://alion.io/job/wonderlic-senior-research-scientist-ai-workforce-intelligence","json_url":"https://alion.io/job/wonderlic-senior-research-scientist-ai-workforce-intelligence.json","meta":{"generated_at":"2026-10-20T00:39:07Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":872,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-21T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":2776658},"rest":"https://alion.io/mcp/rest/get_company?id=2776658"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fwonderlic-senior-research-scientist-ai-workforce-intelligence"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fwonderlic-senior-research-scientist-ai-workforce-intelligence"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fwonderlic-senior-research-scientist-ai-workforce-intelligence"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/wonderlic-senior-research-scientist-ai-workforce-intelligence\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fwonderlic-senior-research-scientist-ai-workforce-intelligence"}]}