In March, I had the honor of representing Icertis at the Women in Data Science (WiDS) Conference held in Pune, India.
WiDS is an exclusive platform blending two very specific topics: Women engineers and the field of data science. It helps address niche issues such as the low number of women that are in technology and specifically the still-nascent data science field.
Having this platform exposes technologists to data science possibilities, while at the same time providing a significant comfort level between the women speakers who bond on many levels beyond simply technology.
This was a tremendous opportunity to represent a company as dynamic as Icertis. The fact that Icertis sponsored such an event shows that the company believes in the talent that women can bring to an organization, and the power of artificial intelligence and machine learning (AI/ML). I was motivated by so many talks and took home even more ideas about implementing new data science algorithms at Icertis, one of which is nearly completed and will be rolled out to management shortly.
There were so many inspiring moments over the conference. A few that stand out:
- It was absolutely humbling and awe-inspiring to be surrounded by women of the caliber of Dr. Rohini Srivathsa, National Technology Officer, India, at Microsoft. She is poised, elegant and knows her material, and she had very inspiring stories about the usage of Microsoft AI/ML for addressing environmental and social concerns.
- I was particularly inspired by Snigdha Gupta from CriXense, who presented an astounding session on the usage of ML to predict cricket match outcomes, including incorporating various factors such as weather, pitch prediction etc. She was an energetic individual and clearly driven by the work she was doing in data science. This talk exposed to me the possibility of how many more ways Icertis can implement data science.
- As a panelist on the discussion “Data Science – A New Raw Material for Businesses,” I got an opportunity to speak about the work we do at Icertis, and how AI in contract management can help businesses negotiate better terms on their contracts. It was a proud moment being able to represent my company in this capacity.
- The floor networking helped me connect with a younger crowd, curious college goers, new graduates, and understand their ideas and dreams. I was bewildered with the enthusiasm this group holds and given an opportunity I would love to be their guide to step into the world of data science.
Women in my circle came to the event only because I was speaking, with the intention of heading off once I was done. Unsurprisingly, they were so inspired by the talks and forum, the 2-hour visit led far into the evening until the event was done at 6 p.m.!
This is the impact of such an event, and the impact of having motivating women on stage. It gets you charged up, it shows you that you don’t have to be a superhero to do something great in data science. It only takes small ideas, working on those ideas and building on each other, and taking the support of your community. Empowering women by supporting each other was discussed during networking, the primary theme being that as women we need to be frontrunners in supporting more diversity in data science field.
Icertis truly believes in increasing diversity within the company, with initiatives specific for women, such as the drive to allow women on a break to rejoin the company in the technology field.
It was an extremely enthusiastic event. The vigorous energy of the speakers and organizers was contagious to the point that the attendees left the conference determined to make a change in at least one aspect of their work. They were motivated to learn new courses and connect with spirited women in their networks. Such initiatives will be the fuel to the fire that drives technology.
Kalpa Ashhar, a senior manager of solutions engineering at Icertis, has over 17 years of experience, 15 years of which have been in the data field. She has two patents to her credit and aspires to continue exploring more innovation in the data field.