Data Scientist I — Healthcare NLQ & AI Solutions

Baylor Scott & White Health; Olympia (WA); On-site; USD 110,000 - 140,000; Full time

Benefits offered by this job

Health benefits

401(k) match

Tuition reimbursement

PTO Day 1

Job summary

Baylor Scott & White Health is seeking a Data Scientist 1 to develop practical data science, NLQ, and agentic AI solutions for complex healthcare problems. You will collaborate with data scientists, data engineers, subject-matter experts, and business partners to frame problems, build reliable models, and deliver AI-enabled insights that improve access to trusted information and reduce manual work.

From problem definition to deployment, you will study NLQ usage, package repeatable work as

Qualifications

• Proficiency in Python and SQL for data exploration, feature engineering, and modeling.
• Experience with statistical analysis, experimentation, and evaluation.
• Familiarity with NLP and machine learning in healthcare context.
• Strong communication and collaboration across technical and non-technical partners.

Responsibilities

• Consult with business, clinical, and technical partners to frame problems and define measurable success.
• Prepare data, engineer features, and build/validate models using SQL and Python.
• Develop NLQ applications and agentic workflows for healthcare questions.
• Evaluate models and agents for accuracy, reliability, and user value; investigate failures.
• Analyze behavioral data to identify unmet needs and translate findings into hypotheses.
• Support experiments and cohort analyses to measure impact of product changes.

Skills

Python

SQL

Statistical analysis

NLP

Machine learning

Communication

Education

Masters or Bachelors + 2 years experience

Tools

Snowflake

Job description

Baylor Scott & White Health is seeking a Data Scientist 1 to develop practical data science, NLQ, and agentic AI solutions for complex healthcare problems. You will collaborate with data scientists, data engineers, subject-matter experts, and business partners to frame problems, build reliable models, and deliver AI-enabled insights that improve access to trusted information and reduce manual work.

From problem definition to deployment, you will study NLQ usage, package repeatable work as