Science
Why we use Science in
our Career Match
most advanced Artificial Intelligence to achieve new levels of
Career Matching.
Understanding what influences human behaviour
Building a robust solution linked to the assessment of potential
Creating a relevant recommendation system
Maximising and enriching the quality of our predictions
What our Science helps you understand
identify candidates matches.
Personality
Personality enables us to understand how a person tends to behave ‘naturally’ and also in stressful situations. A good personality fit means the candidate will feel more comfortable and perform better in their role.
Hygiene Factors
These are the essentials that a candidate needs to be satisfied at work. If these basics aren't right, the career won’t be suitable for them. By assessing these, we ensure the candidate will be comfortable in their role, reducing turnover.
Extrinsic Motivators
Extrinsic motivators include things like financial rewards, job security, and career progression opportunities. Understanding these helps us create job matches that keep candidates motivated and engaged, leading to better performance and job satisfaction.
Intrinsic Motivators
These are the personal satisfactions a candidate gets from their work, such as helping others, social interactions, or solving problems. By aligning these with the job, we ensure the candidate will find the role fulfilling, leading to higher retention and satisfaction.
Why our approach is so unique
the latest App Software & Artificial Intelligence technology.
Behavioural Science Experts
The Science behind our matching was created by a Chartered Psychologist. They undertook over 500 hours of interviews with current professionals and used all their research to build a body of statistical evidence which forms the basis for our matching validity and reliability.
Mobile First & Gamification
We responded to societal and technological developments, where mobile devices are the main tool for media, allowing candidates to complete assessments anywhere and anytime increasing accessibility to historically discriminated groups who are more likely to complete mobile-based assessments.
Career Matching Technology
We have developed a proprietary technology that identifies the personality, hygiene factors and motivation dimensions that determine performance, based on our own research & the extensive ESCO occupational directory. Our model identifies the most predictive dimensions using logistic regression.
Personalised Job Matching
Using our proprietary technology that identifies the personality, hygiene factors and motivation dimensions we determine 40 working traits for every candidate. This allows you to select up to 10 and our model identifies the best match for ur job using logistic regression.
Tech & Science Powering Every Sector,
Now Careers.
The Driving Forces Behind Smarter Decisions and Success in Every Field.
Netflix
Uses these techniques to predict user preferences and recommend movies and shows. It also predicts whether a user will like or click on a specific piece of content.
Experian
Logistic regression is often used in credit scoring models to predict the likelihood of a borrower defaulting on a loan.
Booking.com
Uses these techniques to predict booking behaviors, recommend destinations, and optimise pricing strategies.
Spotify
Spotify uses machine learning, logistic regression, and AI to personalise music recommendations, predict preferences, and create custom playlists.
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