Most skill translation software relies on the common skills associated with a particular military job title. That means the opportunities look exactly the same for anyone with your military job.
They lump you into groups based on occupational specialties, which prevents them from having to do the hard work of understanding you.
You deserve better.
Our goal is to align candidates with company interests and cultural values to find a perfect match. We’ve built assessments to evaluate these attributes:
We believe your experience and interests can align to a job that pays you the most and makes you the happiest. Here’s a sample of output of candidate preferences:
Visualizing what comes next during a career shift can be pretty daunting. That's why we've built technology to predict career paths for military service members. Each stop on the journey is mapped out based on the unique skills and personal values of any candidate.
For example, if a Shift candidate indicates that she is particularly interested in sales roles, then her “sales” dimension is weighted and our predictive technology maps out the possibilities. If she prefers working in small teams, then that dimension is weighted and her career path adjusts accordingly.
It should come as no surprise that our partners (Uber, Affirm, Okta, Major League Baseball, etc.) want to hire a great fit. We work closely with them to understand what teams and managers value and what types of skills they need to grow. Once a candidate completes our career path assessments, we compare their profile to employer profiles generated from surveys completed by all of our partners.
With machine learning algorithms, we're able to recognize patterns, mitigating personal doubt and human error. Every hiring outcome helps improve the accuracy of our predictions, so we can keep helping candidates grow throughout their career :)
We're constantly iterating, so the specifics of our matching technology will certainly evolve. If you’re interested in learning more please reach out to firstname.lastname@example.org.