The Evolving Role of Programming and Data Science in Pharma
Organizers: Albert Man, Shubhadeep Chakraborty
Friday, Aug 21st, 2026
Title: Careers in Data Science: Pharmaceutical & Biotechnology Focus - Discover how your skills can transform healthcare
Speaker: Aron Wisneski, Associate Director
Bristol Myers Squibb
Aron Wisneski is an Associate Director of Statistical Programming at Bristol Myers Squibb, bringing over 25 years of experience in the pharmaceutical industry. Since joining BMS in 2020, he has served as a Therapeutic Area Expert in Cell Therapy, leveraging his deep expertise in statistical programming to drive innovation in one of the most cutting-edge areas of modern medicine. Aron is passionate about the intersection of data science and healthcare, and is dedicated to helping others discover how their analytical skills can create meaningful impact for patients.
Abstract: The biopharmaceutical industry is one of the most impactful arenas for data science professionals. It drives revolutionary medical innovations and offers a growing demand for skills in R, SAS, Python, and AI. This presentation explores how these tools are applied across the clinical research lifecycle — from data collection and processing to statistical analysis and regulatory reporting. Attendees will discover a range of career pathways, from entry-level Statistical Programmer to advanced Data Science Lead. The session will also cover the essential skills needed for success and provide actionable steps for launching or growing a career where data science directly transforms patient outcomes.
Friday, Aug 21st, 2026
Title: Revolutionizing R&D in Pharma with Data Science and AI
Speaker: Aditi Basu, Senior Manager
Bristol Myers Squibb
Aditi Basu Bal is a researcher specializing in machine learning and statistical modeling to extract meaningful insights from complex biomedical data. She is a Data Scientist at BMS Enterprise and holds a PhD in Statistics from Florida State University, along with an Integrated MSc in Mathematics and Computing from BIT Mesra. In her leisure time, she is an Indian classical Odissi dancer, loves exploring new countries, and is often the go-to person for planning memorable travel itineraries.
Abstract: When I entered the pharmaceutical industry as a data scientist with a statistics background, I expected to work mostly with structured clinical datasets and familiar analytical questions, but I quickly realized I had joined the field at a moment of rapid transformation. In just a few years, data science in pharmaceutical research has evolved from supporting analyses to shaping how we generate knowledge across discovery, development, and decision-making. The arrival of generative AI and large language models made that shift impossible to ignore, accelerating new ways to integrate biological, clinical, operational, and real-world data; harness machine intelligence to uncover patterns and generate hypotheses; and support faster, more informed scientific decisions. Recent breakthroughs, from AI-designed therapies advancing into clinical development to multimodal models learning jointly from molecular, imaging, clinical, and real-world data, suggest that the future of pharmaceutical research will depend on how effectively we turn diverse data streams into actionable insight. Just as importantly, that future will be shaped by how quickly, thoughtfully, and efficiently we incorporate AI into every step of our work, from knowledge generation and study planning to analysis, interpretation, and communication. This talk will share that evolution from an early-career perspective and reflect on why this is such an exciting time for students in statistics, data science, and related fields to help shape the future of drug development.