Prakhar Srivastava is a seasoned data science professional currently serving as a Data & Applied Scientist at Zurich North America in Chicago, where he specializes in developing crop insurance and claims recovery models. He brings extensive experience in machine learning and statistical modeling from his previous role as Lead Data Scientist at Discover Financial Services, where he successfully developed advanced credit risk and compliance models.

His professional accomplishments include creating a Long Term Portfolio Risk Score model that achieved 85% prediction accuracy and reduced financial exposure by $198 million over three years. Srivastava demonstrates proficiency in Python, R, PySpark, and model optimization techniques, with applied experience spanning financial services, insurance, and biological modeling domains.

His background reflects a strong combination of technical expertise and business impact focus, with a proven ability to translate complex machine learning concepts into practical, high-value solutions. Srivastava is committed to knowledge sharing and professional development within the data science community, actively seeking opportunities to mentor emerging practitioners in the field.