Assistant Manager, Data Scientist

Relevant years of professional experience in implementing Analytics for business decision support. Experience in implementing statistical/machine learning models like regression (linear, non-linear, mixed models and Bayesian models), classification and unsupervised models i.e., K-Means clustering and Hierarchical clustering in solving key business problems and delivered measurable impact. Clear understanding of statistical concepts and understanding of the underlying assumptions of the models

Good hands on experience in Python, SQL, visualization tools (PowerBI or Tableau), MS Excel, MS-power point (for delivering insights and results)

Collaborating with engineering teams to develop prototypes and software products that can be deployed across varied environments (e.g., cloud, on-premises, devices, etc.)

Implementation experience in at least two topics A. Deep learning concepts (NLP or CV), B. Cognitive cloud APIs from AWS/Azure, C. Docker and D. MLOPs is preferred

Experience in business analytics in US Healthcare.

Ability to handle various data sources (format structured and unstructured; volume sparse and large), using data modeling to develop reporting capabilities and valuable insights across these data sources is key.

Provide increased focus on analytics and emphasize on providing valuable insights to drive improvement opportunities