His academic journey began with a Bachelor of Technology in Computer Science and Engineering from SASTRA University followed by a Master of Science in Management Information Systems, specializing in Business Analytics and Data Science from Oklahoma State University. This strong academic foundation laid the groundwork for his deep analytical and technical capabilities, complemented by professional certifications in AWS Machine Learning, Tableau, and SAS Predictive Modeling.

At Amazon, he served as a Sr. Business Intelligence Engineer in Product Analytics and Data Science, where he was instrumental in influencing measurement strategies, defining success metrics, and implementing best practices around A/B testing and statistical analysis. His leadership in marketing experimentation and data-driven product strategies significantly enhanced business performance, driving a 10% increase in net profit per product and a 30% acceleration in decision-making through advanced data visualization tools. His work in developing scalable A/B testing frameworks and predictive models contributed to deprecating 20% of underperforming products, resulting in a 10% increase in net product profitability. Additionally, his optimization of ETL data pipelines improved data accuracy by 25%, enhancing forecast reliability and operational efficiency.

In his current role as Senior Manager of Data Science, Analytics & Reporting, he continues to excel by driving end-to-end analytics projects in collaboration with Product, Engineering, Marketing, and Risk teams. His expertise in creating and implementing cutting-edge statistical frameworks and experimentation strategies has been pivotal in successful product launches and strategic investment decisions.

Previously, at JP Morgan Chase & Co., he showcased his prowess in risk data science, developing machine learning models that optimized recovery and risk scores, improving liquidation rates by 3%, and saving the company $6 million annually through data-driven strategies. His deployment of a real-time sentiment analysis tool enhanced customer interactions, improving resolution times by 35% and boosting customer satisfaction scores by 20%. His initiatives in automation and process optimization significantly enhanced data quality, operational efficiency, and customer satisfaction, while his market share tool increased management productivity by 10%.

His technical acumen spans a wide array of tools and technologies, including Python, SAS, SQL, AWS, Tableau, and advanced machine learning algorithms like XG Boost, neural networks, and time series modeling. His ability to manage large datasets, automate data pipelines, and develop predictive models underscores his commitment to leveraging data for actionable insights and business impact.

Beyond technical excellence, he is recognized for his leadership, mentorship, and strategic vision. He has a proven track record of guiding cross-functional teams, fostering a culture of continuous learning, and driving transformative initiatives that align with organizational goals. His contributions have earned him multiple accolades, including Amazon Accolades for leadership principles like Earn Trust, Ownership, and Bias for Action, and the 5 Keys of Recognition at JP Morgan Chase & Co. for exceeding expectations and building lasting relationships.

His journey is a testament to his dedication, innovative thinking, and expertise in data science and analytics.