We are seeking an experienced Senior Data Scientist to drive innovation in healthcare analytics using advanced data science techniques, Large Language Models (LLMs), Agentic AI, Natural Language Processing (NLP), and cloud technologies (AWS, Azure, GCP). This role focuses on developing cutting-edge solutions for payers, providers, value-based care (VBC), and population health management.

The Senior Data Scientist will produce innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets. Using a flexible, analytical approach, the Senior Data Scientist will design, develop, evaluate, and deploy robust solutions that leverage innovations in data science, machine learning, and predictive modeling techniques. You will need exceptional skills in statistics, data modeling, advanced mathematics, and programming, along with experience in Generative AI (GenAI) and LLMs. The ideal candidate can work independently and collaboratively across the organization.

Key Responsibilities:

• Problem Definition: Collaborate with product teams and clients to translate real-world healthcare issues into well-defined problem statements and data science solutions.
• Data Cleaning and Exploration: Select appropriate datasets, process and cleanse data for analysis, and develop data structures to organize, collect, and standardize data.
• Feature Engineering: Develop influential features using machine learning and AI techniques to enhance model development.
• Model Development: Build and develop ML/AI models to support our expanding portfolio of healthcare-centric solutions, integrating GenAI and LLMs to enhance data models and algorithms with a focus on natural language processing tasks.
• Model Deployment: Oversee deployment of GenAI and LLM models, ensuring robust monitoring, maintenance, and updates to enhance model performance.
• Model Documentation: Document project development, including problem definitions, data processing, model deployment, and results for auditability.
• Communication of Results: Build presentations, dashboards, and reports to communicate analytical insights effectively to various stakeholders.\
• Mentorship: Serve as a GenAI expert and provide mentorship, peer review, and guidance to other team members.

Essential Duties and Responsibilities:

• Develop and deploy AI agents for healthcare analytics, enabling autonomous decision-making.
• Utilize cloud platforms (AWS, Azure, GCP) to build scalable data analytics pipelines and AI models.
• Apply NLP techniques to extract insights from unstructured healthcare data such as clinical notes and medical literature. Leverage generative AI and NLP techniques to develop predictive models and extract actionable insights from healthcare data.
• Implement text classification, named entity recognition, and sentiment analysis models for healthcare applications across multiple cloud platforms.
• Develop and utilize unit tests to ensure the functional correctness of models.
• Collaborate with cross-functional teams to integrate AI/ML products into existing solutions and workflows.
• Perform exploratory data analysis on high-dimensional datasets, both structured and unstructured.
• Implement text classification, named entity recognition, and sentiment analysis models for healthcare use cases.

Requirements:

• Advanced Degree (Master’s or Ph.D.) in a quantitative field
• 5+ years of experience in data science, with a focus on healthcare analytics and NLP.
• Proficiency in Python, Jupyter Notebooks, and Python libraries like Pandas, Numpy, and Scikit-learn.
• Strong background in machine learning, deep learning, LLM applications, and NLP techniques.
• Experience with cloud services:
  • AWS: Bedrock, SageMaker, Comprehend Medical, Lambda, S3
  • Azure: Machine Learning, Cognitive Services, Azure Functions
  • GCP: Vertex AI, Cloud Natural Language API, Cloud Functions
• Experience using and implementing RAG systems and AI agents.
• Familiarity with healthcare data standards (HL7, FHIR) and regulatory requirements (HIPAA).
• Strong communication skills for presenting complex findings to various stakeholders.
• Experience with big data technologies such as Hadoop, Spark, and distributed computing.

Preferred Qualifications:

• Experience with Epic or other major EHR systems and their unstructured data.
• Certifications in AWS, Azure, or GCP cloud technologies.
• Published research in healthcare data science, GenAI, LLMs, or AI applications.
• Knowledge of medical ontologies (SNOMED CT, ICD-10, RxNorm).
• Experience in multi-cloud environments and building cloud-agnostic solutions.

MedeAnalytics believes in fair and equitable pay. A reasonable estimate of the base salary range for this role is $140,000 - $200,000 USD. Please note that actual compensations for all roles may vary within the range, or be above or below the range, based on factors including, but not limited to, education, training, relevant work experience, professional achievements/qualifications, skill level, business need, location and will be finalized at the time of offer.