Senior Data Scientist

SOLVENTUM•Remote - Pennsylvania, PA

2d•Remote

About The Position

Solventum is a new healthcare company with a long legacy of solving big challenges that improve lives and help healthcare professionals perform at their best. At Solventum, people are at the heart of every innovation we pursue. Guided by empathy, insight, and clinical intelligence, we collaborate with the best minds in healthcare to address our customers’ toughest challenges. 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. As an Data Scientist you will have the opportunity to tap into your curiosity and collaborate with some of the most innovative and diverse people around the world.

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
Must be legally authorized to work in country of employment without sponsorship for employment visa status (e.g., H1B status).

Nice To Haves

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.

Responsibilities

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.