About DOORS

The rapidly evolving job market presents myriad challenges, but also exciting opportunities for improvement and innovation. With increasing demand for specialized roles, employers struggle to find the perfect fit for open positions, while qualified jobseekers may not be aware of unexpected avenues available to them.

With the right tools, we can bridge that gap, helping employers tap into a dynamic workforce and connecting skilled workers with the right employment and training opportunities.

DOORS (“Data for Opportunity in Occupational Reskilling Solution”) provides the tools to build that bridge. It’s is a suite of data-driven tools comprised of two user-facing services digital services that work collaboratively

Recommendation Engine (RecEngine)

For workers seeking out new opportunities, the Recommendation Engine uses personal, governmental, and research data to support their search by:

• Delivering personalized, data-driven career recommendations in growing industries

• Matching users to job opportunities that best fit their skills and professional history

• Highlighting workforce training programs to support new career pathways

The Recommendation Engine uses an algorithm developed by RIPL, fueled by artificial intelligence (AI), machine learning (ML), causal science, and secure cloud computing.

The algorithm pulls data from a user’s resume and other data provided during onboarding, then combines that information with state administrative data on that user’s work history. Cross-referencing this data from multiple sources allows the algorithm to create a unique profile of the user’s existing skills.

Analyzing historical patterns in government data allows Recommendation Engine to predict which career paths and training programs are likely to be the most successful. By comparing a user’s profile to this broader analysis, it’s able to provide users with customized recommendations for better-paying, fulfilling careers with available jobs in their state.

By presenting this information to jobseekers through user-friendly digital services, our goal is to empower workers to leverage their own skills and learning opportunities to find enriching, lasting careers.

ReadyHire

On the hiring side of the equation, ReadyHire uses scientifically grounded and ethical machine learning to match employers to work-ready jobseekers the skills they need.

ReadyHire cross-references job descriptions with state administrative data on candidate work history to find matching skillsets, then presents an anonymized candidate pool for the employer to browse for qualified jobseekers. By keeping candidates anonymous and focusing on skills first, the service encourages high-quality job matches that might not have occurred using traditional hiring practices.

Employers can browse and compare multiple anonymous candidates by skillset to find the best matches. Once they’ve selected the candidates they’re interested in hiring, ReadyHire contacts those individuals via text or email. Contacted jobseekers can choose whether or not to reveal their personal information to the employer and move forward with the application process.

ReadyHire gives employers access to new candidate pools and enables them to zero in on qualified workers in a more direct and efficient way. Our goal with ReadyHire is to support high-quality job matches that might otherwise be lost in the noise, while also streamlining state labor department-run job placement programs.