Divanshu Mittal is a seasoned Data & Machine Learning Engineer with over 15 years of professional experience driving advanced analytics, statistical modeling, and AI/ML-powered insights across the healthcare, finance, and public sectors. With a proven track record in leveraging data to fuel business success, Divanshu brings deep expertise in pricing analytics, clinical data processing, and scalable data solutions to help enterprises make smarter, faster decisions.
Currently serving as Senior Data Analyst and Pricing Analyst at Cardinal Health, Divanshu has led the development of robust pricing guidance systems using machine learning and statistical techniques, generating over $5 million in additional profit margins. His focus areas include loss prevention, profit opportunity identification through share-of-wallet analytics, and automation of contract pricing validations. His work has helped enhance compliance, improve margins, and scale insights for high-impact decision-making.
Divanshu’s technical acumen spans SAS, R, Python, SQL, Google BigQuery, Tableau, Power BI, and ETL/data warehousing technologies. He has engineered web-based pricing tools, built data ingestion pipelines, and implemented predictive modeling systems using Python and SAS that align with enterprise business goals.
Previously, as a Clinical SAS Programmer at Iqvia (formerly Quintiles), he contributed to Phases I–IV of clinical trials, developing and validating critical datasets like ADaM and SDTM. He also ensured compliance and quality across safety and efficacy reports. His career foundation in financial analytics at Wells Fargo saw him deliver HAMP-related metrics and loan performance insights through advanced SAS reporting and macro programming.
Divanshu holds a Master’s in Analytics from Dakota State University and a Master’s in Public Administration from California State University, Long Beach, showcasing a unique blend of data science proficiency and strategic policy insight.
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Divanshu continues to thrive as a leader in data innovation, empowering enterprises with data clarity and actionable insights. His drive to extract meaningful intelligence from complex datasets positions him as a vital contributor to modern data-driven organizations.