- Recognitions: 2024 President’s Award Winner, Q1 2024 & Q4 2023 Excellence Award Nominee- Delivering significant cost savings by enhancing customer experience, reducing agent cognitive overload, and optimizing business processes, all through innovative data-driven strategies and advanced analytics.

Team: Marketing Analytics- Analyzed business data to provide insights that support decision-making and improve business processes. - Collaborated with cross-functional teams, ensuring that data-driven insights help drive company growth and operational efficiency.

• Improved overall efficiency by developing a custom search algorithm to re-allocate trips of private charter operators using Python.• Saved $150,000+ worth of empty flying for private charter operators by proposing business recommendations and generated additional revenue of $60,000.

• Developed a scoring system for promising investments with statistical scoring models using Python.• Prioritized investment options by strategic filters through SQL queries on >1 TB database.• Compared and analyzed property features and price trends through visualizations on Tableau.

• Led a large-scale effort to predict the world-wide absolute poverty at a granular level, assembling extensive data, building visualization models, and using cognitive analysis in order to estimate missing data using Python.• Forecasted the evolution of poverty in the world using supervised machine learning models (Automated ARIMA and VAR).• Detected trend anomalies and outliers by building data visualization dashboards using Tableau.Part of Operations Consulting Coursework at Columbia University.

• Optimized JetOps flight scheduling system, predicted on-time rate for 83% of the flights and decreased the delay compensation by 30%.• Conducted feature selection by feature importance, and selected variables such as plane type, day of the week, humidity, wind speed.• Implemented Decision Tree, Random Forest, Gradient Boosting, and Neural Networks models using Python; Compared runtime, accuracy, confusion matrix, and ROC curve, and selected Gradient Boosting model.Part of Operations Consulting Coursework at Columbia University.

• Acquired the first costumers of the company by developing a strategy to research, test and select new acquisition channels.• Improved marketing strategy by implementing dynamic A/B testing on selected acquisition channels (Google analytics).Part of Operations Consulting Coursework at Columbia University.

6-week long internship through the University of Tokyo Summer Internship Program. I worked with Prof. Yasushi ONO on Toroidal Magnetic Field Measurement in Magnetic Reconnection Region in Plasmas.The following objectives were accomplished: • Conducted experiments with 6 individuals to generate data (1M+) for multiple integrator channels and multiple configurations, handling all aspects of cleaning, preprocessing, and data streamlining while under strict deadlines and heavy workloads.• Predicted % conversion of magnetic field energy into kinetic energy and heat using Scikit-learn library of Python.UTSIP Program: UTSIP Kashiwa, initiated by the Graduate School of Frontier Sciences in 2013, provides a hands-on research internship program to approximately 35 students in total in various departments. On the final day of the UTSIP Program, participants give a presentation summarizing their research and findings from the program.

10-week long internship through the S.N.Bose Scholarship Program. I worked with Prof. Francis Halzen at Wisconsin IceCube Particle Astrophysics Center(WIPAC) on Simulations and Statistical Data Analysis of Flat-Spectrum Radio Quasars. The following objectives were accomplished: • Simulated data sets (2.5M+) obtained by Wisconsin IceCube Particle Astrophysics Center using Cosmic Ray Simulation Kascade (CORSIKA), a Monte-Carlo simulation software. • Cleaned, Preprocessed, pipelined and visualized generated data using matplotlib and seaborn libraries in Python.I also learned the following:• The theory on the need for neutrino astronomy, atmospheric neutrinos and muons, cascading equations, neutrino sky, possible sources, point sources searches, Quasars and point sources search techniques with the focus on STACKING.• The basics of simulating software CORSIKA (Cosmic Ray Simulation for KAscade), a Monte-Carlo program where different interaction models, atmospheres and cosmic ray models can be used, to check self-veto probability.S.N.Bose Scholars Program: To nurture future innovators and thought leaders, the Science & Engineering Board (SERB), Department of Science and Technology (DST), Govt. of India, the Indo-U.S. Science and Technology Forum (IUSSTF) and WINStep Forward have partnered to develop a dynamic and transformative student exchange program between premier institutions in India and the United States.