Sep 2021 – Jul 2024 · 2 yrs 10 mos · Noida, Uttar Pradesh, India · Hybrid

• Worked in the core Data Science Practice Team at Inshorts.We did a lot of cool experiments like:
• 1. A User Profiling and News Recommendation Engine :Built a personalized dynamic news recommendation engine algorithm for close to 100 million users modeled by a graph based inferential approach and user profiling through a cluster based distribution analysis over their individual timespents spread across active articles at any given moment.
• 2. A News Notification Engine : Developed an efficient notification engine to deliver daily news updates, leveraging a powerful news classification algorithm. The implementation led to a remarkable 6.8% increase in average DAU, driving significant inorganic user engagement.
• 3. A News Categorization, Summarization and Tagging Engine: Worked on implementing sharp generative AI models to automate news summarization and tagging. The solution would generate concise 60-word conceptual summaries and keyword tags, eliminating the need for manual intervention. These automated summaries will facilitate seamless article search and collaborative content aggregation.

Aug 2019 – Aug 2021 · 2 yrs · Gurugram, Haryana, India

• Worked in the Data Science Practice team in the Centre of Excellence (COE) group of the organization. Responsible for researching, developing and implementing solutions to real world business problems across a wide range of business domains with an emphasis on the areas of Machine Learning, Decision Optimization, Predictive Modeling, Forecasting, Metaheuristics, Deep Learning
• 1 ) Personalized Recommendation Engine : Built a product recommendation engine for boosting store sales through customer interaction and targeting customer retention through personalized offers. Increasing customer cart values using recommendations based on collaborative filtering, content based filtering, graph theory, guided selling and customer segmentation.
• 2) Last Mile Delivery Optimization: Optimized last mile delivery with multiple hubs delivering goods for multiple customers in a city in their preferred time window. The solution helped minimize the operational costs, maximize resource utilization and serve customer demand on time.
• 3) Inventory Management : Built reinforcement learning agent solution to determine the optimal level of inventory for thousands of products. The solution prevents understocking and overstocking leading to better utilization of the capital invested and improving order-fulfillment by delivering within the committed lead times.
• 4) Real Time Flexible Scheduling : Created a meta heuristic solution using evolutionary algorithms for optimal scheduling of large scale manufacturing orders. The solution reacts to dynamic changes in the manufacturing environment such as inflow of orders, machine breakdown, resource unavailability, production delays etc to create an optimal job schedule. It minimizes the makespan, tardiness(total delay) and maximizes the resource utilization.

Jul 2019 – Aug 2019 · 1 mo · Gurugram, Haryana, India

Jan 2019 – Jun 2019 · 5 mos · Bengaluru, Karnataka, India

• Developed explainable machine learning models to detect potential loan defaulters for a leading bank in Singapore.. The models rendered actionable insights to evaluate credit risk strategies and mitigate bad loans.