Senior Data Scientist

Solventum

Data Scientist specializing in medical document analysis at Solventum. Developing advanced NLP/NLU systems for healthcare decision making with cutting-edge AI technologies.

Posted 6/3/2026full-timeRemote • Pennsylvania • 🇺🇸 United StatesSenior💰 $124,000 - $170,500 per yearWebsite

Tech Stack

Tools & technologies

AWSCloudETLPySparkPythonPyTorchSpark

About the role

Key responsibilities & impact

Scoping and designing NLP/NLU applications that support clinical understanding of medical documents and downstream healthcare workflows.
Translating business and clinical requirements into mathematical and experimental criteria, ensuring models are measurable, reliable, and auditable.
Processing, aligning, and enriching diverse structured and unstructured medical datasets for deep learning, LLMs, and agentic AI systems.
Developing and evaluating deep learning models, including transformer-based architectures and neural architectures such as CNNs and attention mechanisms for capturing linguistic patterns in clinical text.
Understanding and mitigating model weaknesses, including bias, drift, hallucination behavior, and robustness concerns.
Designing experiments and error analyses that explain model behavior and enable clear communication with both technical and non-technical audiences.
Deploying models into Solventum’s cloud environment, partnering with ML engineering to ensure reliability, observability, and compliance within regulated healthcare systems.
Staying current with emerging research in NLP/LLMs, evaluating new methods and identifying opportunities to advance Solventum’s deep learning initiatives.

Requirements

What you’ll need

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.

Benefits

Comp & perks

Medical, Dental & Vision
Health Savings Accounts
Health Care & Dependent Care Flexible Spending Accounts
Disability Benefits
Life Insurance
Voluntary Benefits
Paid Absences
Retirement Benefits

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Pythondeep learningNLPNLUtransformer-based architecturesCNNsattention mechanismsstatisticsexploratory data analysisETL

Soft Skills

self-organizationcommunicationclarityconfidence

Certifications

Master's degreePhDBachelor’s degree