Mentor Selection Process at GreyAtom

. 3 min read

Today, online learning has helped students personalize their learning process. Students get to choose from a variety of course providers, and have substantial control over their schedules and pace of learning. But the most pertinent way in which classroom learning still scores over online learning is, the presence of the tutor. The tutor’s presence means the students’ concerns are readily addressed, and that each student can be dealt with empathetically. Online learning institutions have been trying to incorporate this experience with online mentors for quite a while now, the success or failure of which depends heavily on the mentor. So, we take our mentor selection process seriously. All our mentors are selected through a detailed process as given below.

The mentor selection process at GreyAtom:

Reach out to qualified professionals
We consider various online and offline sources for shortlisting potential mentors like LinkedIn, Twitter, Slack channels, coding communities like GitHub, internal references, etc. Shortlisted candidates usually have an industry experience of at least three years as a Data Scientist with hands-on experience in NLP, ML and/ or DA. We initiate communication with them asking for their interest in mentorship.

If they express interest, the following information is provided.
• Objectives of the Program
• Program curriculum
• Requirements from the mentor throughout the program

First level call with the mentors:
The first level is primarily to assess the soft skills of the mentor. If the person does not have previous mentoring experience, we evaluate the mentor’s communication skills and intent to teach/ mentor. The mentor should be able to reach different kinds of students and be able to deal with them with patience and empathy.  We make sure we select mentors whom the students will find relatable in terms of knowledge and skill.

Second Level Call with Mentor Candidates:
A Subject Matter Expert from GreyAtom has another round of discussion with the candidate to understand their educational background, technical expertise and industry experience. People with experience in hiring activities are preferred, as they would be aware of industry requirements and are better suited to train students on similar lines. Onboarding experience is also a plus, meaning they have experience is bringing peers, employees or students up to speed on relevant skills.

Practical Evaluation:

Webinars are a great way to evaluate mentors.


As a teacher, Albert Einstein could not attract a lot of students. There was no lack of knowledge or experience, but that his teaching skills were amiss. Not everyone who is technically strong can be a good teacher or mentor. Therefore, we evaluate the candidate’s teaching skills through an actual classroom session, where they will be handling a group of learners from varied backgrounds and levels of expertise. A team of experts will be present to evaluate the candidate, and the feedback from the learners is also incorporated in the selection process.

We evaluate the mentors on the following points:

  • Learning plan/ outline for the subject - It should cover all pertinent topics and have a logical flow from start to end.
  • Communication and Interaction - The mentor should be able to speak clearly and effectively, and should be able to intrigue the students, maintain their interest, and glean interaction from them. We see how they are able to accommodate students of varying levels of proficiency.
  • Relevance, veracity, and depth of subject matter - The content should be relevant as on date, it should be accurate and deep enough that learners feel they have derived value.
  • Exercises, Coding and hands-on sessions for students - The mentor should be able to share practical use cases and coding examples from across different business scenarios. Mentors at GreyAtom should be able to write, teach and solve coding issues real-time.
  • Doubt Resolution - Ability of the mentor to handle questions from students and give satisfactory responses is paramount.
    Students are asked to give feedback on the mentor. Candidates who get a 4 or above out of 5 are selected for the final meeting.

Finalizing Mentorship:
Once the mentor has been finalized, we have elaborate meetings where we onboard the mentor with GreyAtom's vision, philosophy and core values. We make sure that our priorities are in sync, where in we operate with a goal to impact learners' life through quality practical education.

Mentors are then onboarded with GLabs, (GreyAtom’s learning platform) and the course material. GreyAtom takes utmost care in designing the courseware, and is done with the help of industry experts. The mentor’s feedback on the same are also incorporated if necessary. And once the mentor is comfortable with our working and platform, they are assigned lighter topics and batches, gradually moving to more demanding coursework.

Interested in the joining a program? Check out our Data Science Masters Program and our Frontend Developer Program!



Get Started - Future proof your career

Join 150,000 aspirants. Learn Today - Apply Today. Try Free Programs

Learn Data Science Free with GLabs