Note: The job is a remote job and is open to candidates in USA. Baylor Scott & White Health is a not-for-profit healthcare system focused on improving the well-being of individuals, families, and communities. The Clinical Data Scientist will collaborate with research teams to address complex clinical challenges by developing AI/ML, generative AI, NLP, imaging, and clinical data solutions that support research, decision-making, and patient outcomes.
Responsibilities
- Communication and Clinical Consulting: Translate complex data science and machine learning concepts into clear, actionable insights for clinicians, researchers, and non-technical stakeholders. Present data-driven findings to support clinical decision-making, research initiatives, and operational improvements
- OpenAI and Generative AI Applications: Design, develop, and deploy solutions leveraging large language models (LLMs), including OpenAI-based systems, to extract insights from unstructured clinical data. Build prompt-driven and programmatic pipelines for clinical text understanding, information extraction, summarization, and decision support. Ensure responsible and effective use of generative AI in healthcare and research settings
- Natural Language Processing and Generative AI: Design and implement NLP pipelines leveraging transformer architectures (e.g., Clinical BERT, ModernBERT) and large language models (LLMs, including OpenAI-based systems) to process clinical notes, imaging reports, and other unstructured EHR data. Develop explainable AI solutions to support clinical interpretation and research
- Medical Imaging and Multimodal Data Analysis: Apply machine learning techniques to imaging data (e.g., echocardiography, ECG, radiology reports) and integrate multimodal data sources to enhance disease detection, phenotyping, and predictive modeling
- Data Engineering and Pipeline Development: Design and maintain scalable data pipelines for clinical and research data, integrating diverse sources such as EHR
- Data Collection and Optimization: Extract, clean, and analyze data from SQL-based systems (MS SQL Server) and cloud-based environments like Microsoft Azure
- Research and Innovation: Contribute to clinical research initiatives, including study design, model development, validation, and manuscript preparation. Stay current with advancements in AI/ML, clinical informatics, and digital health to continuously improve methodologies
Skills
- • Master's degree in a quantitative field like computer science, engineering, statistics, mathematics, economics, or a related field
- • 3+ years of hands-on data scientist mathematical predictive modeling experience in a business environment or equivalent
- • Proficiency in common language/tools for AI/ML – (e.g., Python/Pyspark, Keras, Tensorflow libraries, etc.)
- • Experience working in a cloud environment such as Azure, and their ML services
- • Great social skills, like communication and partnership, are needed. This is due to interaction with analytics, intelligence, and cross-functional teams
- • Know algorithms for advanced analytics, like binary classification, regression, Neural Networks, and Natural Language Processing
- • Demonstrated knowledge of software engineering topics, including classes, functions, version control, CI/CD, and unit tests
- • Technical expertise with many compute environments
- • Experience working in EDW cloud technologies - Snowflake
- • Proven experience in working with large datasets and relational databases (SQL)
- • EDUCATION - Masters' or Bachelors plus 2 years of work experience above the minimum qualification
- • EXPERIENCE - 3 Years of Experience
- PhD preferred
Benefits
- Immediate eligibility for health and welfare benefits
- 401(k) savings plan with dollar-for-dollar match up to 5%
- Tuition Reimbursement
- PTO accrual beginning Day 1
Company Overview
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