Many shoppers don’t realize that data science is a key player in retail. This field helps businesses understand consumer habits, predict product demand, set prices, and streamline transportation of goods.
Data scientist Vivek Anand is a prime example. As the director of data science at the Gap, a San Francisco-based clothing retailer, he leads a team focused on using data to enhance company operations.
Anand highlights an essential aspect of data science: “It’s about solving problems that seemed impossible before.” His team analyzes various transactions to reveal underlying similarities, helping the company make informed decisions.
With a rich background in data science, artificial intelligence, and statistical modeling, Anand plays a significant role in shaping the retail industry. His impressive work earned him the AI100 award from AIM Research, recognizing him as one of the top AI leaders in the U.S.
Anand’s journey began in Gopalganj, India, where he initially dreamed of becoming a doctor. He enrolled in the Indian Institute of Science Education and Research in Pune to pursue medicine. However, he discovered his passion for mathematics in his first semester. A project focusing on vaccination strategies showed him how much he enjoyed using math for solving real-world problems.
After graduating in 2011 with degrees in mathematics, Anand pursued a master’s in operations research at Columbia University. There, he learned how to gauge people’s risk tolerance for investment decisions. His education, combined with an internship at an investment firm, led to his first job at Markit, now part of S&P Global. He focused on creating models for pricing various financial instruments.
After starting as an analyst in 2013, Anand quickly climbed the ranks to become an assistant vice president by 2015. He then joined Citigroup, where he developed data models for bond pricing and led a team focusing on credit derivatives.
In 2018, Anand transitioned to Zilliant, a consultancy in pricing and revenue optimization. As the lead data scientist, he improved pricing models for various industries. His work on estimating price elasticity, which predicts how demand shifts with price changes, greatly sped up processes that once took days to compute.
Now at the Gap, Anand oversees three key areas: price optimization, inventory management, and fulfillment. He highlights the challenges of managing a fashion retail inventory, particularly since most items are manufactured overseas, leading to long delivery times. Anand emphasizes the need to optimize inventory, ensuring they don’t have too much or too little of any product.
He notes that effective data models often outperform traditional expertise. Instead of relying only on average delivery times, advanced data science can provide a more accurate estimate and help in making smarter buying decisions.
Recently, Anand joined IEEE, encouraged by his wife, computer engineer Richa Deo. He found it challenging to connect with fellow professionals in the emerging field of data science until he reached out to IEEE members through her network.
He remarked, “IEEE helped me build the professional connections I was looking for.” This network has been invaluable as he continues to innovate in retail through data science.
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