Qlearsite recently held a talk at one of London’s well known universities, the London School of Economics, for masters students studying Human Capital Management. Our talk was based on what Qlearsite as a company does as well as our technology and functionalities, and how Natural Language Processing (NLP) can be powerful and utilised in the HR space. It was a great evening with lots of interesting conversations around not just NLP in the HR space, but also around how to get started in a data analytics consulting career.
Here are some of the questions we were asked by the students:
Consultant/ Job Role Questions
How did you get your job?
As a data analytics consultant the short answer to how I got my role was through looking at online vacancies for different types of consultancies. When I was initially applying to different roles I focussed more on larger consultancies, and I didn’t know much about data analytics - until I found Qlearsite.
Do you need a specific degree to become a data analytics consultant?
For consulting roles, there isn’t a specific degree that is requested. I personally studied Economics in university, which well equipped me when it came to my approach in analysis and numbers. That being said, having studied a degree which gives you background in analytics, the functions of HR or business would help to equip you for the role.
What is your day to day role as a consultant?
Everyday is different which is what I love most about my job! Although projects and clients differ, my main role is working with our clients to deliver people insights and analysis for their organisations - I help them make better, informed decisions about their people using data to back it up. This includes having discussions with clients, answering any questions they may have around our technology and tools and giving presentations of their reports to their executive teams.
In addition to this, I also write articles and thought pieces around subjects that impact people in the workplace - from frameworks to national days (e.g. international women’s day) which are published on Qlearsite’s blog. As a consultant I also have input in the development of our consulting products, for instance the question sets and frameworks. I love the variety!
What type of companies are best to work with and why?
I love all our clients equally - however, clients who are ready for change and willing to take significant actions based on the findings we give them are always the best. They’re willing to listen and take on board feedback given to them, which you know will positively impact the experiences of their workforce. I also have great appreciation for clients who see the value in the technology we provide to them, and find it as exciting as we do!
Qlearsite Framework Questions
Do you only use your QlearFit® framework? What else do you do?
We have a range of products and services available - along with the standard reports we create, we also work on bespoke projects depending on client needs. Our platform allows you to not only analyse survey responses but also deploy surveys and create invites and reminders for participants. We also have a prediction tool which can predict the impact that trends or initiatives can have on your organisation - for example, you can see which factors within your organisation may predict attrition.
How do you guard against bias in your NLP?
Our tool is constantly being updated and improved by our team, and everyone in our company actually has input into the machine learning process. Our organisation is diverse and we all make the time to label data to help guard against bias, so that it’s not just the same people teaching our machine.
How do you calculate the scores on your QlearFit framework?
As a rule of thumb we focus on the favourability of responses - the proportion of those who agree and strongly agree to the closed text questions. The overall QlearFit score is the average favourability across the 16 indicators.
Can you analyse external data?
Absolutely, we are able to analyse historical surveys that were not deployed by us.