Principal Data Scientist

About Providence

Providence, one of the US’s largest not-for-profit healthcare systems, is committed to high quality, compassionate healthcare for all. Driven by the belief that health is a human right and the vision, ‘Health for a better world’, Providence and its 120,000 caregivers strive to provide everyone access to affordable quality care and services.

Providence has a network of 52 hospitals, 1,000+ care clinics, senior services, supportive housing, and other health and educational services in the US. 

Providence India was established to bring to fruition the transformational shift of the healthcare ecosystem to Health 2.0. The India center will have focused efforts around healthcare technology and innovation, and play a vital role in driving digital transformation for Improved patient outcomes and experiences, caregiver efficiency, and running the business of Providence at scale.

Why Us?

  • Best In-class Benefits
  • Inclusive Leadership
  • Reimagining Healthcare
  • Competitive Pay
  • Supportive Reporting Relation

Principal Data Scientist – JD


We are seeking a highly skilled data scientist with a PhD in a quantitative field to join our team. The ideal candidate will have a strong background in statistical modelling and machine learning, and experience working with large datasets. Experience with patents and published whitepapers is preferred.


As a Principal in Data Sciences, you will

  • Contribute to creating a robust vision for AI/ML team within Providence India. Maintain healthy backlog of futuristic product features and technical capabilities. Perform and set review standards, own Healthcare marketing models complicated (For Ex: Propensity models, Lead scoring algorithm, Next Best Action model, Response and Utilization models) and help the team with design and development approach as needed.
  • Engage with Providence stakeholders to define use case for model development globally and influence decisions related to marketing measurement, audience targeting, channel strategy and Martech product features, and priorities.
  • Create forecasting and machine learning models by working alongside with business stakeholders in Marketing, Strategy and Digital experience to solve their business questions.
  • Partner with multiple cross-functional global teams like product managers and data analytics engineers in deriving insights, presenting, and documenting the findings.
  • Design and implement experiments to test hypotheses and validate models.
  • Hands-on experience with latest MLOPs tools like Databricks, Microsoft Azure Machine learning studio or similar in deploying models at an enterprise scale.
  • Show an ever-learning mindset to strengthen understanding of global health care systems. Participate and contribute to industry learning and stay up to date with latest trends and findings.

Who are we looking for?

  • 12 years+ industry experience with PHD in a quantitative field such as Data Science, Computer Science, Statistics, Physics, Economics, Analytics, or other science, math, and technology intensive field.
  • Should possess strong math, technology, business, and communication skills.
  • Extensive experience in conducting diverse statistical analyses of complex, high dimensional datasets and preparing reports and visualizations to support findings. Demonstrated expertise in Machine Learning via Python or R.
  • Experience in developing & deploying machine learning models using modern, open-source tools and frameworks. Experience in Deep learning is a plus.
  • Experience in applied statistics skills, such as distributions, statistical testing, regression, etc.
  • Ability to translate complex statistical concepts into easily understandable language for non-technical stakeholders.
  • Familiarity with cloud computing platforms such as AWS, Snowflake or Azure
  • Experience with big data technologies such as Hadoop, Spark, or NoSQL databases
  • Background in healthcare system or marketing is a plus.


At Providence, we not only acknowledge differences but also honor it. We appreciate differences related to the following factors but not limited to background, education, gender, age, generation, religious background, ability, technical skills in all our employment related opportunities.

Health is a human right