Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Baylor Scott & White Health
- *About Us**
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.
Our Core Values are:
+ We serve faithfully by doing what's right with a joyful heart.
+ We never settle by constantly striving for better.
+ We are in it together by supporting one another and those we serve.
+ We make an impact by taking initiative and delivering exceptional experience.
- *Benefits**
Our benefits are designed to help you live well no matter where you are on your journey. For full details on coverage and eligibility, visit the Baylor Scott & White Benefits Hub to explore our offerings, which may include:
+ 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._
- *Salary**
The pay range for this position is $90k annually (entry-level qualifications) - $140,462k annually (highly experienced). The specific rate will depend upon the successful candidate's specific qualifications and prior experience.
- *Job Summary**
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.
- *Essential Functions of the Role**
+ **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.
- *Key Success Factors**
+ Master's degree in a quantitative field like computer science, engineering, statistics, mathematics, economics, or a related field. Significant demonstrated experience in the role. 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.
+ 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).
- *Belonging Statement**
We believe that all people should feel welcomed, valued and supported.
- *QUALIFICATIONS**
+ EDUCAT