Enabling better, smarter, safer healthcare to improve lives.

Data Scientist – Medical Document Analysis

Data ScientistData ScientistFull TimeRemoteTeam 10,001+H1B No SponsorCompany Site LinkedIn

Location

Minnesota

Posted

53 days ago

Salary

$106K - $145.8K / year

Postgraduate Degree5 yrs expExperience acceptedEnglishAWSETLPy SparkPythonPy TorchSpark

Job Description

• As a Data Scientist specializing in medical document analysis, you will work at the forefront of healthcare NLP. • You will design, implement, and evaluate advanced natural language understanding (NLU) systems that interpret complex clinical text and support data-driven medical decision making. • This includes developing models grounded in transformers, generative AI, and research-oriented neural architectures. • You will collaborate closely with clinical domain experts, fellow data scientists, ML engineers, and product teams to bring research prototypes into production systems. • You will explore new modeling approaches, optimize training pipelines, and contribute to the long-term direction of Solventum’s deep learning portfolio.

Job Requirements

Master's degree or PhD in computer science, mathematics, or related fields or Bachelor’s degree with at least 5 years of IT experience
Solid experience in Python especially in deep learning for text analysis and libraries such as PyTorch and Transformers
Solid grasp of statistics and exploratory data analysis
US citizenship or permanent resident required
Experience conducting research-driven NLP/NLU work involving representation learning, attention mechanisms, or hybrid neural architectures.
Ability to self-organize across multiple technical and business contexts, communicating complex findings with clarity and confidence.
Experience extracting insights from complex clinical datasets and presenting those insights to varied audiences.
Familiarity with AWS, GitHub, CI/CD, and scalable ML deployment practices.
Hands-on experience with LLMs, prompting, fine-tuning, or agentic AI frameworks.
Experience with ETL of large-scale text using tools such as PySpark, Spark NLP, or distributed data frameworks.
Exposure to clinical coding systems or medical terminologies (e.g., ICD, CPT, SNOMED) is a plus.