Data Scientist (Healthcare Domain)

Must Have: Data Scientist, AI ML, Epic Clarity clinical data models

1. Work with Customer stakeholders to document and understand their objectives and ideate how AI/ML solutions might achieve those objectives.
2. Perform exploratory data analysis to understand the data available related to a particular business objective and if that data lends itself to the creation of an AI/ML solution that might achieve that business objective.
3. Optimizing Large Language Model (LLM) output with prompt engineering; building (RAG) pipelines.
4. Build AI/ML models that attempt to address a business objective given the data available; explore the model space to understand the optimal model for the particular use case and what the performance characteristics are.
5. Create repeatable, interpretable, and scalable models that can be seamlessly incorporated into analytic data products.
6. Engineer features by using business acumen to find new ways to combine data sources.
7. Write production-quality pipeline code used to load data, execute the AI/ML model, and store the results.
8. Perform analyses of AI/ML models and systems, such as fairness, bias, and equity audits; performance analyses; impact assessments; and interpretability reports.
9. Develop and commit Python code in such a way that it works in harmony with the code and systems being developed by the team s data engineers, software engineers, and data analysts.
10. Plays a key role in communicating ML/AI methodology and impact to senior management to inform strategic decision-making.
11. Proactively communicates with stakeholders about areas of concern regarding changes in work schedules.
12. Leads and manages complex projects, including managing multiple stakeholders and teams. Build and maintain relationships with key stakeholders, including senior management and clients.
13. Mentors and coaches junior team members on ML/AI techniques and best practices. Leads and motivates project teams by setting clear goals and expectations. Builds and maintains strong relationships with key stakeholders across the organization.
14. Other duties and/or projects as assigned.
15. Adheres to Customer Organizational competencies and standards of behavior.

Education, Knowledge, Skills, and Abilities Required:

1. Bachelor's degree in STEM or another related/relevant field of study.
2. Minimum of 4+ years of experience working in a data science role; or 5+ years of experience working in a data engineering, analyst, or architecture role.
3. Extensive Python development experience.
4. Extensive SQL experience.
5. Proficient in developing and interpreting complex statistical models and a wide range of ML models.
6. Excellent understanding of most aspects of clinical data; Very proficient with querying and using clinical data.
7. Able to deploy custom ML/AI models to a cloud platform. Proficient in writing production code for complex models.
8. Experience and ability to optimize LLM output with prompt engineering, model fine-tuning, and ability to create RAG pipelines.
9. Can create custom model monitoring solutions as needed.
10. Work effectively with team members and technical and non-technical stakeholders.
11. Excellent written and verbal communication skills.
12. Proficient computer skills including but not limited to Microsoft Office and Google Suite platforms.

Education, Knowledge, Skills, and Abilities Preferred:

1. Master s / PhD.
2. Minimum of 5+ years of data analysis experience in healthcare.
3. Proficiency in Epic Clarity clinical data models.
4. Experience with Google Cloud Platform (Big Query, VertexAI, etc).
5. Experience with Git and GitHub.
6. Experience with Docker.

Licenses and Certifications Preferred:

1. Epic Clarity Data Model.
2. Epic Clarity Clinical Data Model.
3. Google Machine Learning Engineer Certification.