Rishi Kulkarni, PhD

VP, Engineering and Machine Learning, Data Science, Credenza

Education:
PhD, University of California, Berkeley; B.A., Boston University
Location:
Boston, MA
Rishi Kulkarni, PhD

Highlights

  • Supported the development of machine learning algorithms to streamline clinical trials, R&D, and workforce management, among other processes
  • Research focus in areas ranging from nonparametric estimation to computational chemistry and biology
  • Strong foundation in Bayesian statistics, model prototyping, and data product lifecycles
  • Consistent contributor to open source projects used across the data science ecosystem, including SciPy, Airflow, and Numba

Experience

As the Director of Data Science at Credenza, Rishi leads a team of data scientists and engineers and works across multiple teams to develop and deploy machine learning algorithms for dynamic pricing and healthcare workforce management, and to support other key business initiatives. Rishi’s leadership and experience has had a direct impact on solving process inefficiencies, generating gross profits, and improving both client satisfaction and worker experience.

Rishi has over 10 years of experience in medical research and data analysis. As a Senior Data Scientist for Tessella, he partnered with pharmaceutical clients to streamline clinical trials, reduce costs for SME recruitment, and improve overall time-to-market for new pharmaceuticals. Rishi has also worked as a postdoctoral researcher at Stanford University, a graduate student researcher at U.C. Berkeley, and a research assistant at Boston University. While at U.C. Berkeley, he taught undergraduate courses in organic chemistry and chemical biology.

Rishi’s passion for data science has led him to present the topic at various national and international conferences.

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