Summary
Palak Bansal is a data scientist who blends machine learning, statistics, and causal inference with hands-on software development in Java and Python. Based in New York, she currently applies ML at CVS Health while pursuing an MS in Data Science at NYU. Her graduate research at NYU focuses on Generative AI and Causal Inference, including recovering Average Treatment Effect with high precision using PyTorch and non-gradient optimization techniques. She has built a versatile portfolio from NLP, anomaly detection, and real-time insights at SAP to causal inference and ATE applications during internships at Raven Industries and NYU, with 8 years of experience in data science. Palak’s mix of academia, industry, and a strong foundation in data-driven decision making enables her to ship practical, scalable solutions across healthcare, tech, and finance domains.
9 years of coding experience
4 years of employment as a software developer
Master of Science - MS, Data Science, 3.89, Master of Science - MS, Data Science, 3.89 at New York University
Bachelor of Technology, Information Technology, 8.46, Bachelor of Technology, Information Technology, 8.46 at Manipal Institute of Technology