Career Recommendations
Match every student to high-fit roles and skills, then map the courses, micro-credentials, and experiences that raise employability and confidence.
Role & skills match from coursework, projects, and interests
Gap analysis → recommended courses, badges, internships
Real-time market signals (demand, salary range, growth)
Personalized "career pathway" with milestones & nudges
Advisor/career coach feedback and approvals
A career-matching engine that learns from students
A career-matching engine that learns from each student's academic history, projects, interests, and strengths to recommend roles and the concrete steps to become competitive.
Analyzes coursework, projects, and interests for high-fit role recommendations
From skills profile to career readiness
Builds a live skills profile from the Common Data Model, aligns it to labor-market taxonomies, identifies gaps, and suggests courses, micro-credentials, and experiences, plus sample resumes and outreach templates.
See how it works
Watch career recommendations in action
Key capabilities
From skills mapping to career-ready artifacts
Skills graph
Builds a comprehensive mapping of student competencies from coursework, projects, extracurriculars, and credentials into a dynamic skills profile.
Labor market alignment
Matches student skills to real-time job market data including demand trends, salary ranges, and growth projections from industry sources.
Gap analysis
Identifies skill gaps between a student's current profile and target roles, then recommends specific development paths to close those gaps.
Opportunity discovery
Surfaces relevant internships, job openings, programs, and micro-credentials aligned to each student's skills and career interests.
Education-to-employment pathways
Maps clear pathways from current coursework to target careers, showing which courses, credentials, and experiences lead to employment outcomes.
Industry trend analysis
Tracks emerging industry trends and evolving employer requirements to keep career recommendations aligned with where the job market is heading.
High-impact use cases
From exploration to job-ready preparation
Career exploration
First-year student explores "What can I do with a Psychology major?" System shows 15 roles with fit scores, salary, and demand.
Skills gap closure
Junior wants to become a UX designer. System recommends 2 courses, 1 micro-credential, and a summer internship to close the gap.
Resume generation
Student uploads transcript; system drafts a skills-based resume highlighting relevant coursework and projects for target roles.
Career coach support
Advisors review AI-generated pathways, add local employer contacts, and approve final plans before students apply.
Outcomes you can measure
Proven results from institutions using Career Recommendations
Improved career readiness
Of students actively explore career pathways and report feeling better prepared for the workforce.
Better job placement rates
Increase in graduates securing roles aligned to their skills and career goals within six months.
Data-driven career guidance
Students and advisors make decisions backed by real-time labor market data and skills analytics.
Workforce-aligned curriculum
Of programs use career insights to align curriculum offerings with real workforce needs and employer demand.
Connects to student and market data to keep recommendations real and current
Career Recommendations integrates with academic and labor-market systems
Common Data Model
Pulls transcripts, course catalogs, project portfolios, and internship records to build comprehensive skills profiles.
Labor Market APIs
Integrates with Lightcast, O*NET, LinkedIn Talent Insights, or Burning Glass to surface real-time job demand and salary data.
Credential Platforms
Syncs with Credly, Badgr, or institutional micro-credential systems to recommend and track badge completion.
Human-centered, fair, and private
Built with student agency, bias mitigation, and data protection at the core
Student agency & transparency
- Students and advisors approve plans and artifacts before use
- Transparent rationale for role matches and micro-credential picks
- Appeal and override options with comments and version history
Privacy & bias mitigation
- RBAC, least-privilege access, audit logs on generated artifacts
- Bias checks across programs/cohorts; PII minimization
- Aligned to FERPA/GDPR and institutional data-sharing rules
Implementation timeline
From taxonomy mapping to campus-wide rollout in 6–8 weeks
Taxonomy & data setup
- Map courses and projects to skills taxonomies
- Integrate labor-market API (Lightcast/O*NET)
- Configure role libraries and salary benchmarks
Pilot with cohort
- Test with 100–200 students across 3–5 majors
- Generate pathways and gather feedback
- Tune matching algorithms and role rankings
Career center training
- Train advisors on reviewing AI-generated plans
- Configure approval workflows and overrides
- Add institutional employer contacts and resources
Full rollout
- Enable for all students campus-wide
- Launch self-service career exploration portal
- Monitor usage, bias metrics, and iterate
Frequently Asked Questions
Ready to align programs with real careers, and give students a clear plan to get hired?
See how Career Recommendations can improve student outcomes and employability