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Shilpi Bhadra

Lead Data Scientist

Shilpi Bhadra is a self-motivated and business-savvy data scientist with a diverse background in collaborating with various groups within business and IT ecosystems to establish best practices for analytics projects in Financial (Capital Market & Asset Management) and Utilities domains.

With a strong expertise in developing predictive modeling methods and tools, Shilpi has a history of designing data mining and analytics projects to address strategic business needs and improve system performance by implementing efficiency enhancements.

Shilpi boasts extensive experience in creating platforms for energy demand response optimization, dynamic price performance analysis, and utilizing smart grid analytics with a focus on CIM Integration standards.

Proficient in a wide array of skills including hypothesis testing, graph modeling, multivariate testing, and optimization algorithms, Shilpi is well-versed in descriptive, exploratory, inferential, and predictive modeling while excelling in data aggregation and reduction techniques for large datasets using R.

With proficiency in tools like R-Studio, Tableau, and MS Excel, as well as a familiarity with SQL/PL SQL, RDBMS, and Big Data Analytics in the Hadoop ecosystem, Shilpi has contributed significantly to developing data definitions for databases and executing high-performance analytical projects.

Having completed a Bachelor of Engineering from Allahabad University in Electrical Engineering at Motilal Nehru National Institute of Technology, Shilpi further pursued a Master's degree at NYU Stern School of Business.

Shilpi Bhadra has held various key roles throughout their career, serving as the Lead Data Scientist at Photon and being associated with organizations like Cygnus Professionals Inc., Jean Martin, IBM, Softnet Technology, and Salora International Ltd.

Academically inclined with a deep professional acumen, Shilpi's expertise spans predictive modeling, machine learning, data mining, and a multitude of analytical techniques utilized across different industries and domains.

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Location

Greater New York City Area