Intuit India recently hosted the highly anticipated Women in Data Science Worldwide (WiDS) Bengaluru 2025 conference on June 12, which brought together over 140 data science professionals from academia, startups, GCCs, and IT services. Held at Intuit’s Bengaluru office, the event served as an inspiring platform for professionals to connect, learn, and explore the future of AI and machine learning in an inclusive and dynamic environment.
As the global financial technology platform behind TurboTax, Credit Karma, QuickBooks, and Mailchimp, Intuit is firmly committed to driving innovation in data science. The WiDS conference, initiated by Stanford University, has grown from a one-day event into a global movement, reaching over one lakh professionals annually through conferences, datathons, podcasts, workshops, and programs aimed at fostering the next generation of data scientists.
The event kicked off with opening remarks from Vignesh Subrahmaniam, Intuit’s WiDS brand ambassador, who set the stage for a day of enriching discussions. Subramaniam highlighted the groundbreaking contributions of Florence Nightingale, the first woman to apply statistics and data science to improve healthcare and her innovative use of data revolutionised healthcare decision-making, establishing a powerful legacy for data-driven solutions in the field.
Subramaniam’s words set the tone for the conference, reminding attendees of the pioneering role women have played in shaping the world of data science.
Insightful Sessions and Keynote
The keynote session by Amruta Joshi, managing director of AI Solutions at Google, was a deep dive into what is tangible innovation. Sheoffered clarity on the role of embedded systems, delegation, and the current limitations of AI. This session resonated deeply with attendees, who were encouraged to focus not just on AI’s potential but on practical, creative applications that could lead to real-world impact.
One of the standout sessions was led by Sridhar Dasaratha, head of AI research at EY, who posed the crucial question: How can large language models (LLMs) be effectively applied in finance? Dasaratha emphasised the need for grounding AI-generated answers in factual data, minimising hallucinations, and ensuring that generation only occurs when the model has genuine knowledge. This session sparked deep discussions on the importance of data integrity and accuracy when using AI in high-stakes fields like finance, where precision is non-negotiable.
Next, Jayashree Mohan from Microsoft Research took the stage to address LLM serving and the system design challenges it presents. She discussed the latest advancements in scalable training and efficient inference techniques, such as FlashAttention, vLLM, Orca, and TokenWeave. Mohan also highlighted the critical role of performance analysis tools like LLM Judge and LMSYS-Chat-1M. Her message was clear: robust infrastructure is the key to achieving reliable and scalable AI performance, not just faster models. Her session captivated the audience, stressing that scalability is essential for real-world applications.
Anjaly Parayil, from Microsoft Research, stressed that fairness in AI systems should be integrated throughout the design process, rather than being added as an afterthought. She introduced FairServe, a framework designed to ensure equitable LLM access amidst competing demands. Using mechanisms like overload-driven throttling, debt-based prioritisation, and weighted service counters, FairServe ensures fair access in AI systems. Parayil session sparked a lively discussion on how to balance efficiency with equity in AI-powered systems.
Later in the day, Sid Kumar and Arkadeep Banerjee from Intuit provided a simplified visual explanation of reinforcement learning from human feedback (RLHF). Banerjee further introduced the Data QnA mindset, emphasising the importance of context, relevance, and cohorts when handling data.
He pointed out that while RLHF is a powerful method, there are scenarios where non-RLHF methods are more suitable, particularly when simple feedback suffices. Their session was a perfect blend of theory and practical application, offering valuable insights into context-aware AI systems.
The conference wrapped up with a session by Niyati Chhaya, co-founder of Hyperbots, who discussed the inherent messiness of invoices and human interactions in the finance sector. She highlighted the need for developing agentic workflows in finance that take into account unstructured data, trust establishment, and validation processes.
Chhaya’s talk provided a roadmap for streamlining complex financial tasks, emphasising that AI systems must be designed to handle the nuances and complexities of real-world data.
A Day of Inspiration and Collaboration
The WiDS Bengaluru 2025 conference was a resounding success, offering an enriching mix of insights, discussions, and networking opportunities.
The sessions covered critical topics ranging from LLM applications in finance to AI fairness and system design, all contributing to the future of data science and AI. Attendees left feeling inspired and empowered to push the boundaries of innovation in data science.As Intuit continues to champion diversity and inclusivity in AI, the WiDS Bengaluru 2025 conference was a testament to the growing role of women in shaping the future of technology. Stay tuned for the next edition, where industry pioneers will continue to share cutting-edge knowledge, empowering you to thrive in a rapidly evolving landscape. Learn more at Intuit careers.
The post Intuit India Champions Data Scientists at WiDS appeared first on Analytics India Magazine.
