Data Scientist
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Job Description
Data Scientist designing and implementing AI and advanced analytics solutions for cancer care. Collaborating across teams to develop models and validate AI systems.
Responsibilities:
- Collaborate with administrative leaders, clinicians, researchers and engineering teams
- Query and interpret large clinical and operational data sets
- Develop machine learning pipelines, AI/LLM tools and agents, and statistical analyses
- Design and implement AI and ML validation frameworks (experiments, pilots, metrics)
- Partner with engineering teams to move solutions into production platforms and environments
- Produce technical documentation and presentations
- Project management; independently decompose requests into project tasks and manage time
- Independently research business and clinical problems and associated data sets
- Performs other related duties as assigned or requested
Requirements:
- Master’s degree with 0+ years of experience; or Bachelor’s degree with 3+ years of experience
- Familiarity with a health care environment and EHR data
- Expertise with or more data science domains (time series, deep learning, LLM architectures, Natural Language Processing (NLP), causal inference, etc.)
- Familiarity with cloud services like Microsoft Azure and version control systems (Git)
- Experience with Generative AI and Large Language Models (LLMs), RAG, fine-tuning, embeddings, prompt engineering, and agentic workflows
- Experience with data science/AI product lifecycle and understanding model training, testing, deploying, and monitoring
- Awareness of the most recent trends and developments in Artificial Intelligence
- Proficient developing machine learning models for classification, regression and clustering
- Experience with relational databases and SQL queries
- Proficient in Python and its machine learning libraries like pandas, scikit-learn, PyTorch, etc.
- Experience designing AI solutions, applying python LLM frameworks like LangChain and LangGraph, and designing tools, skills, and/or subagents for AI frameworks
- Knowledge of probability, statistics, and scientific computing
- Ability to work independently and use creative approaches to problem-solving
- Capable of turning questions into testable hypotheses, extracting data from complex databases, creating and evaluating statistical models
- Experience in data visualization and ability to communicate results to a non-technical audience
- Experience completing independent research and development with limited supervision
- Experience being part of large, cross-functional teams with many internal and external teams involved
- Experience with Agile project management frameworks and Jira is a plus
Benefits:
- Comprehensive Benefits
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