Clinical Data Scientist

Here at Baylor Scott & White Health we promote the well-being of all individuals, families, and communities. Baylor Scott and White is the largest not-for-profit healthcare system in Texas that empowers you to live well.

About the role

The Clinical Data Scientist will collaborate closely with research teams to address complex and high-impact clinical challenges. The ideal candidate will be well-versed in Python and AI/ML frameworks and skilled with generative AI tools, with familiarity in software engineering. This expertise will support clinical research, inform decision-making, and drive improvements in patient outcomes.

Responsibilities

• 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.
• 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.
• 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.
• 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.
• Design and maintain scalable data pipelines for clinical and research data, integrating diverse sources such as EHR.
• Extract, clean, and analyze data from SQL-based systems (MS SQL Server) and cloud-based environments like Microsoft Azure.
• 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.

Requirements

• Master's degree in a quantitative field like computer science, engineering, statistics, mathematics, economics, or a related field. PhD preferred.
• 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.
• Strong communication and partnership skills, due to interaction with analytics, intelligence, and cross-functional teams.
• Knowledge of 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: Master's or Bachelor's plus 2 years of work experience above the minimum qualification.

Benefits

Our benefits are designed to help you live well no matter where you are on your journey.

• 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

Note: Benefits may vary based upon position type and/or level.

Pay

The pay range for this position is $90,000 annually (entry-level qualifications) - $140,462 annually (highly experienced). The specific rate will depend upon the successful candidate's specific qualifications and prior experience.