Georgette Virgo
Photo Courtesy of Niloy Gupta
Accessing precise data has always been the cornerstone of informed decision-making, yet achieving this level of accuracy once required painstaking manual analysis and significant time investments. However, advancements in machine learning (ML) and artificial intelligence (AI) have profoundly changed how businesses gather, interpret, and act on data.
Niloy Gupta, with a Masters from the School of Computer Science at Carnegie Mellon University, Pittsburgh, and now a staff machine learning engineer and tech lead at Attentive Mobile, has worked on these technologies in different industries, such as advertising, e-commerce, finance, and pharmaceuticals.
With a patent application for a large-scale simulation system for financing program optimization and an open source for “Efficient Online Inference of Gradient Boosted Tree Models,” and previously as chief technology officer and co-founder at Lambent Logic, his decade of experience showcases the ability of these technologies to enhance user engagement and business outcomes.
“Traditional data analysis methods couldn’t keep pace with modern business demands,” Gupta explains. “Modern ML systems can process billions of data points in milliseconds, delivering precision that was previously unimaginable, delivering greater value to businesses.”
Precision: Knowing the Business Better
Understanding the market is the key to any business success, but with thousands of variables influencing consumer behavior, pinpointing specifics can be a daunting task. Traditionally, businesses relied on generalized information to make decisions, often missing the nuances that drive customer preferences and purchasing habits.
However, the advent of AI and ML has transformed this process, enabling companies to analyze vast datasets and extract actionable insights with precision. Gupta explains that these technologies allow businesses to go beyond surface-level trends, uncovering the more complex patterns and preferences that shape market dynamics.
For instance, in his work at Lambent Logic, Niloy Gupta developed a sophisticated data analytics system that streamlined revenue management for life sciences companies. Pharmaceutical manufacturers in the U.S. lose $15 billion annually due to revenue leaks. Niloy Gupta leveraged advances in distributed computing, AI/ML, and state-of-the-art algorithms to develop a platform that could identify leakages in pharmaceutical supply chains. This helps pharmaceutical companies optimize drug prices, making them more accessible to the consumer while meeting government regulations.
“AI and ML give businesses the ability to understand the business and consumers better,” Niloy Gupta shares. “AI/ML is a powerful tool to optimize a business’s operations.”
How Precision Drives New Opportunities
Technologies today not only help businesses understand their current markets but also enable them to tap into new, unexplored opportunities. These advanced algorithms and data-driven insights identify potential customer segments that were previously overlooked, expanding their reach and driving growth. Gupta experienced how this capability is particularly valuable in industries like online advertising.
His work at Yelp exemplifies how technologies can unlock new market potential. During his time at the company, Gupta developed a solution to enhance the accuracy of click-through rate (CTR) prediction models used in online ad serving. These models were instrumental in determining which ads should be shown to users by predicting their relevance to individual user intent. He combined feature engineering, statistical analysis, and ensemble learning with distributed system performance tuning to create a system that improved ad targeting and optimized bidding strategies in auctions.
This innovation allowed Yelp to connect advertisers with potential customers more effectively, ensuring ads reached the right audience at the right time. It has resulted in improved revenue metrics by 10%.
“The more accurate the CTR prediction, the better we can ensure users see ads they’re interested in while maximizing value for advertisers,” Gupta adds. This approach enhanced user satisfaction and opened up new revenue streams for businesses by enabling them to reach untapped audiences.
Lowering Risks and More Targeted Decision Making
From advertising and eCommerce, AI and ML could also drive precision in finance and credit underwriting, as highlighted in Gupta’s work in building ML pipelines for underwriting and fraud detection models at Affirm. By leveraging ML, Niloy Gupta was able to develop models that could analyze vast amounts of data, identify complex patterns, and make predictions with high accuracy.
This precision is crucial in underwriting, where accurate risk assessments are essential for lenders to make informed decisions about loan approvals and terms. Similarly, in fraud detection, ML models can quickly identify anomalies and inconsistencies in data, allowing for more effective fraud prevention and mitigation.
According to Niloy Gupta, this capability not only improves the accuracy of underwriting and fraud detection but also enables lenders and insurers to make faster, more informed decisions. By automating routine tasks and focusing on complex cases, AI/ML prevents human error in the process, leading to more precise and effective risk management strategies.
A Work in Progress
Despite his contributions to using AI and ML, Gupta recognizes that precision is still a complex goal and can often be achieved on a case-to-case basis. However, the machine learning engineer is optimistic about AI/ML’s current capabilities and the future innovations they promise. From fraud detection to precision medicine and automated decision-making, these benefits can provide significant cost savings to businesses.
As he continuously works with AI and ML, Niloy Gupta is eager to expand his expertise and contribute to driving precision further across diverse sectors. He envisions a future where these technologies not only achieve accuracy but also reliability. He strives to expand his knowledge and adapt to technology, ensuring that AI seamlessly enhances business operations with real-time insights for smarter decisions.
Gupta mentions, “The ultimate goal is not just precision but empowerment. When businesses have access to precise data at their fingertips, they can innovate faster, serve their customers better, and create lasting value.”