Jul 2024 – Jan 2026 · 1 yr 6 mos · Remote

• 1. Advised and partnered with C-suite leaders at top U.S. banks to define enterprise AI strategy; delivered 20+ GenAI education sessions (Agents, RAG, Fine-tuning, etc.) to 1,000+ professionals, accelerating adoption of AI across business functions.
• 2. Led architecture deep-dives for production-grade AI workloads, enabling scalable solutions in chatbots, credit modeling, fraud detection, and agent-based automation across 20+ financial institutions.
• 3. Developed 10+ GenAI proofs-of-concept (RAG and Agents), contributing to a 40% year-over-year increase in Azure consumption within client organizations.

Feb 2022 – Jul 2024 · 2 yrs 5 mos · New York City Metropolitan Area

• 1. Spearheaded the development of a groundbreaking strategy to measure the efficacy of AI products, leading to a 2X increase in ROI and enhanced data-driven decision-making. (Patent Granted)
• 2. Led the development of a personalization engine in Azure and AWS using deep learning models, achieving a 6X increase in net new assets and demonstrating robust and agile project management skills. (Patent filed)
• 3. Built an ML-powered product tailored for small business owners prospects by integrating external and internal datasets through fuzzy matching and Python-based APIs. This targeted approach increased small-business engagement, catalyzing a 2X expansion in business growth.

May 2020 – Feb 2022 · 1 yr 9 mos · Princeton, New Jersey, United States

• 1. Designed a BERT-based classification system on GPU platforms, enhancing patient experience categorization and driving client revenue growth by 20%
• 2. Developed a prospecting model utilizing TensorFlow k-means clustering to efficiently target and prioritize potential leads, improving the conversion process by 2X.
• 3. Led a hybrid cloud migration strategy employing Kubernetes, focusing on optimizing for GPU cloud instances. This strategy ensured the seamless integration of on-premise data centers with cloud technology.
• 4. Analyze and visualize data for various clients to drive business and marketing decision-making; created a dashboard to capture patient journeys and highlight product performance against competitor product lines.

Feb 2019 – May 2020 · 1 yr 3 mos · New York City Metropolitan Area

• 1. Developed and optimized RNN and LSTM time-series forecasting models to
• enhance client demand planning, reducing write-offs by 35%.
• 2. Developed a proof of concept for detecting similarity in the launch trajectories of different products in different markets by leveraging various clustering techniques.
• 3. Outlined AI project scopes and established roadmaps for effective resource management
• allocation, supporting clients in formulating benchmark strategies, and assessing
• AI project ROI.

May 2018 – Aug 2018 · 3 mos · New York City Metropolitan Area · On-site

• I was selected for the prestigious summer leadership program, where I led a project to predict the probability of claims for vehicle policies. By analyzing data in R, SAS, and SQL, I developed a risk scorecard that reduced operational risk by 20%. My findings were presented to the executive team, including the CEO and CFO, showcasing the impact of data-driven insights on strategic decisions.

Dec 2017 – Dec 2018 · 1 yr · New Jersey

• Researched, designed, and implemented advanced machine learning systems using predictive modeling and natural language processing.
• Managed Big Data for training and deploying ML/NLP solutions, enhancing business modules and search bots.
• Conducted data cleansing, feature engineering, and statistical analysis to support R&D initiatives.

May 2017 – Sep 2017 · 4 mos · Rutgers,New Brunswick

• Accomplished CITI training to get access to MIMIC-III data.
• Data Wrangling for the purpose of prediction and analysis.
• Logistic Regression was employed to predict the mortality of ICU patients using various vital signals.
• Data Visualization was performed using Tableau.