Our Meet the Team series showcases the brilliant and talented experts at Virtualitics who are dedicated to empowering organizations with AI-driven analytics and applications.
“Our team takes problems that our customers are facing and then ideates, implements, and deploys solutions for them,” explains Anubha Bhargava, a data scientist at Virtualitics. “Customer feedback is integral to our process so we make sure to integrate their ideas and suggestions throughout our data science efforts.”
Anubha grew up near Boston, Massachusetts, where an early love for math and playing with Legos naturally guided her toward a career in engineering. She majored in electrical engineering at Rensselaer Polytechnic Institute (RPI), then completed her master’s degree at Columbia University, where she discovered the vast potential of data science.
“I knew I needed to pivot into this space,” Anubha says. Since shifting her focus, she has developed a wide range of predictive models, helping businesses across defense, health, wellness, and marketing optimize their strategies. “I built models that predict the likelihood that a customer would purchase a fitness membership and at what price point, as well as a recommendation system that helped users find the best subject line for emails.”
When Anubha brought her talents to Virtualitics, she was heartened by the company’s values of innovation and inclusivity.
“I was looking for a company where I could work on exciting projects from start to finish. I was fortunate to not only find this at Virtualitics, but also become part of a workplace that supported me when I was a new mom and again, when I returned to work after maternity leave,” she says.
Making a Difference in Work and Life
Since joining Virtualitics, the data science team has doubled in size, a testament to the rapid expansion and increasing demand for data science expertise. Currently, Anubha is working with the IRO Workforce team to develop a topic modeling solution that fuses qualitative insights from large volumes of text with quantitative workforce readiness metrics. “This innovation will help businesses optimize their resources, resulting in more effective scheduling and cost savings,” she explains.
Her experiences as a mother have also influenced her professional work. She recently developed a machine learning model that predicts a baby’s birth weight, which can help parents and doctors better prepare for pregnancy, labor and delivery, and newborn care. The model is based on open-source data from Kaggle on comprehensive factors such as time since last pregnancy, mother’s birthplace, father’s education, and more. By taking all this into account, the model provides insights on the risks and outcomes of pregnancy and birth based on whether the baby will be born underweight or overweight. Anubha was invited to present her work at the 2024 Grace Hopper Celebration, the world’s largest gathering of women and nonbinary technologists. Being able to share her work on a global platform is a huge honor!
As Anubha continues to use her innate curiosity for building things that make a difference, she remains a powerful role model for women in tech—demonstrating that it’s possible to excel in a demanding industry while embracing all the facets of life, inside and outside the office.
