Niranjan Saigaonkar

Led over 10 GenAI and data transformation programs for global pharmaceutical clients, generating approximately $7M in booked revenue and influencing over $7.5M in pipeline through enterprise AI platforms and advisory services. Directed a global regulatory analytics transformation, delivering a foundational data platform, an LLM-based data remediation engine, and three activated use cases.

Prepared data from raw files with over 39 billion data tuples using SAS and SAS Data Integration Studio. Built classification models for proactive prediction of disease conditions with 96% accuracy, reducing model run time from 72 hours to 6 hours.

Designed an improved plant layout, reducing manufacturing process time from 3 days to 1 day using simulation theory. Eliminated engineering bottlenecks by transitioning to 3D modeling techniques, which reduced rework by 83% and led to savings of over 20%, approximately $600,000.

Negotiated commercial and legal contracts for capital equipment worth $514 Million, resulting in savings of over $32 Million. Analyzed technical requirements and suggested cheaper equivalent materials, leading to additional savings of over $8 Million.

Developed an advanced analytics-based patient journey and treatment gaps solution using Real World Data for a top pharma client. Created a Precision Medicine Program roadmap to guide the development of precision medicine capability in cancer care.

Automated brand performance dashboards for an oncology business unit, leading to the release of 7 FTEs per brand from daily reporting. Developed a market penetration dashboard along with strategic actions for brands approaching patent expiry.

Designed and deployed a Medical Monitoring & Clinical Data Review application suite with a factory onboarding model, enabling scalable ingestion of clinical trial data across multiple studies and reducing setup time by 40%. Automated study-level data onboarding using robotic process automation (RPA) and metadata-driven pipelines, cutting manual configuration time by 60%.

Grade: 3.77

Completed a Master of Engineering in Industrial & Systems Engineering. Achieved a GPA of 3.77.

Grade: 3.7

Obtained a Bachelor of Engineering in Mechanical Engineering. Achieved a GPA of 3.7.