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 121,000 caregivers strive to provide everyone access to affordable quality care and services.

Providence has a network of 51 hospitals, 1,000+ care clinics, senior services, supportive housing, and other health and educational services in the US.

Providence India is bringing 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 of health systems 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

**What will you be responsible for?**
- As a Principal Data Scientist, you will be responsible to develop effective and high-quality healthcare program integrity analytics that meet business requirements. Technical abilities include following Python/R coding best practices, performance tuning, unit testing and production support. In Addition, your responsibilities include:

- Performs advanced statistical analyses to identify patterns and trends and opportunity assessments to assist in delivering optimal healthcare management and decision making.
- Designs data visualizations and determines the best way to present data in a clear understandable format using reports, drilldowns, tables, gauges, graphs, charts, and other intuitive graphical add-ons.
- Experience working with Gen-AI, expertise in fine-tuning transformer-based models / LLMs
- GPT, Llama, PaLM, BERT and RAG models.
- Fine-tuning of Large Language Models (GPT/ PaLM/ Llama) to meet specific business requirements.
- Develop and implement machine learning models using a variety of techniques (supervised and unsupervised learning models including NLP, Deep learning Models, and Predictive Analytics)
- Ensure accuracy of data and deliverables of reporting employees with comprehensive policies and processes.
- Manage and optimize processes for data intake, validation, mining, and engineering as well as modelling, visualization, and communication deliverables.
- Prepares and delivers results to leadership with analytic insights, interpretations, and recommendations.
- Understanding data storage and data sharing methods.
- Understanding healthcare business operations.
- Strong proficiency in: Python, PySpark, SQL, R & have experience in machine learning libraries & frameworks such as TensorFlow, PyTorch, or Keras.
- Deep expertise in traditional as well as modern statistical & ML techniques like regression, support vector machines, Regularization, Boosting, Random Forests & other ensemble methods.
- Proficiency in developing NLP models using: Nltk, spacy, Genism, Word 2 Vec, Seq 2 seq, transformers, BERT etc.
- Prior hands-on experience in analysing large and complex data sets, data reliability analysis, quality controls and data processing, with focus on model validation practices.

**Who are we looking for?**
- 12 yrs. of professional work experience preferable in management consulting or high growth start-ups preferably in healthcare and 8-12+ years of experience in a data analytical role.
- Bachelor's degree in mathematics, statistics, healthcare administration, or related field.
- Master's degree advantageous.
- 5+ years of experience in Python, SQL, R, SAS
- Designing, developing, and implementing AI/ generative AI models & algorithms to solve complex problems and drive innovation across organization.
- Lead all stages of AI/ML solutions implementation: Gathering business requirements & understanding, data requirements for the solution build, any constraints (data /business), data exploration/solution design, machine learning models development, active collaboration with model risk team to ensure high quality model deployment & minimize enterprise risk.
- Lead the implementation of AI solutions to deliver business impact with focus on value, success criteria alignment, scalability, and operationalization.
- Collaborating with cross-functional teams to define project requirements and objectives, ensuring alignment with overall business goals for integration, sign-off and deploying machine learning models into production.
- Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.
- Engage team members, project managers & business stakeholders in the analysis and interpretation of experimentation results & ensuring feedback is incorporated as appropriate into models.
- Drive best practic