Data Science Isn't Just for Tech Companies; Nitish Gaddam Applies Technical Solutions to a Myriad of Business Challenges

Nitish Gaddam

As a professional data scientist and machine learning expert, there's nothing Nitish Gaddam loves more than getting in front of a computer screen, writing a creative code script, and changing how a business runs. It might seem far-fetched that programming languages can be that impactful, but in today's digital world, it's these types of tools and capabilities that are making the biggest changes across every single industry.

With a bachelor's degree and a master's degree in computer science, Nitish brings his full-stack Data Science capabilities to the table in any situation. He can use SQL to build a database, turn to Python to automate a major task or use Flutter & Javascript to update a website, but that's just the beginning. His skills span broader and deeper, working with cloud databases, machine learning algorithms, and converting cutting-edge research into operational data products with ease. Even before all of these advanced technological capabilities existed, Nitish was using technical tools as a college student to solve business problems in India.

When he was in college, the problems he was solving were different from the ones he works through today, but the way he thinks about problem-solving hasn't changed much since then. Helping small businesses build websites, stand up digital marketing channels, and create e-commerce offerings, was the most effective way to bring them into the digital age. He knew that nearly any business problem could be solved with a technological solution he just had to figure out the "how."

Today, as a data science professional, Nitish finds himself working on the "how" every day. At Paypal, in his last role as a senior data scientist, Nitish was tasked with collecting and analyzing user insights that would help drive business outcomes. He tested how users interacted with the platform, collected data surrounding their behavior, and derived insights from that data to help Paypal boost revenue numbers. With advanced machine learning algorithms, Nitish tested a variety of product mixes and determined optimal sales goals for overall business success.

Prior to Paypal, at eBay, Nitish worked with the affiliate marketing team to develop the optimal bidding strategies for different marketing campaigns. Though the application was different, he used similar machine-learning tools to conduct experiments, test outcomes, and understand campaign effectiveness. These tools enable extensive testing and data collection, making it possible to make business decisions faster and with more accuracy than any human team could do alone. To manage the enormous amount of data that was collected during this testing, Nitish also had to build and structure database systems that were capable of handling this level of volume.

Throughout his career, Nitish has found himself in thought leader positions with a variety of organizations. Just like in college, he helps businesses address their problems with new technological solutions. He has partnered with organizations in the entertainment space, the business intelligence space, and even the education industry, proving that technological solutions have a place in all industries. Every business faces challenges, and with passion and skill, Nitish gets to help advance his clients from one hurdle to the next.

Working with large companies and startups can be two very different experiences, but to Nitish, it doesn't matter whether the organization is large or small. What matters is that he has the right tools and capabilities to prosper, and he's committed to making that happen. No matter how complex a data set is or how difficult an algorithm might be to build, he's excited by the opportunity to solve for the "how" and make a difference.