AI in Recruitment – Understanding Designations and Skills

13, October, 2017


Artificial Intelligence - Consumer - Featured -


Relevance of jobs for candidates and candidates for recruiters is the most important challenge for AI in recruitment. Whether it is an Application Tracking System or a job portal, recruiters want easy mechanism to identify the most relevant candidate. That said, only a recruiter knows what they want. An AI Algorithm only knows the job description which it shares with the system (there are still gaps that exist between what the recruiter wants and what the description says).

Over the last few years, this has been area of major focus and attention for the team at Naukri.com. Discussed here some elements which are important in solving this challenge.

Challenge 1: Complexity of Indian Economy – No one sector or industry dominates

India is a large country with several 100 industries and sectors with companies of varying size. Every organization has many unique roles and designations that employees carry. Even within the organized sector, we have more than few 1000 roles and may be more than 50,000 designations. AI Algorithms need to understand what each of the designations stand for.

 Challenge 2: Creative Designations

Every organization is creative with designations and often internal designations are created to balance the organization challenges and individual aspirations. In many companies, Software Developers carry the designations like Software Engineer, SSE -1, SSE -2, Member of Technical Staff. However, few companies call their Quality Engineers as Software Engineers.

Often designations are created to represent evolving role descriptions based on the unique organization requirements. For example, a few years ago, Mid-Office was created as a designation to distinguish teams from Front Office and Back Office. Similarly, we have seen new age professions emerge, for example, Digital Marketing, SEO Specialist, Social Media Marketing Manager, Data Scientist and so on.

For a system to understand the requirement, AI Algorithm must first understand the designations and the similar designations or related designations which other companies may have.

Challenge 3: Some Designations carry no information about role

Often designations are devoid of specific domains and also, role information. Some jobseekers write designations as Vice President, Manager, Senior Manager, Officer etc.

Challenge 4: Skills, Regions, Divisions are part of Designations

Skills are also part of designations which are often used to differentiate employees in the same role with specialized focus skills or areas of responsibility. For example, Software Developer, C++ Developer, Java Developer, Senior Engineer- COBOL and so on. In the sales function, there are many designations like Sales Regional Manager, Territory Manager – Bhopal, Area Sales Manager- Mangalore, Regional Manager – Paints and Specialty Chemicals etc. As we can observe, Cities and business units have been appended to these designations to differentiate sales managers playing similar roles with special focus areas.

The challenge to disambiguate designations is not trivial as new designations are created on an ongoing basis. Skills are often used by jobseekers to distinguish themselves vis-a-vis other jobseekers.

AI algorithm needs a library of Designations & Skills and their inter-relationships. Have we solved the matching problem with regards to designations and skill sets? Maybe to a large extent. Yet there is scope of improvement and our effort continues. There are many other elements which play an important role in identifying relevant candidates, which I intend to talk about in later articles.

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Originally published on The Desk of Vivek Jain in collaboration with Info Edge