Description

Thank you for your interest in joining Solventum. 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. While we continue updating the Solventum Careers Page and applicant materials, some documents may still reflect legacy branding. Please note that all listed roles are Solventum positions, and our Privacy Policy: https://www.solventum.com/en-us/home/legal/website-privacy-statement/applicant-privacy/ applies to any personal information you submit. As it was with 3M, at Solventum all qualified applicants will receive consideration for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Job Description:

Data Scientist for Medical Document Analysis (Solventum)

3M Health Care is now Solventum

At Solventum, we enable better, smarter, safer healthcare to improve lives. As a new company with a long legacy of creating breakthrough solutions for our customers' toughest challenges, we pioneer game-changing innovations at the intersection of health, material, and data science that change patients' lives for the better while enabling healthcare professionals to perform at their best. Because people, and their wellbeing, are at the heart of every scientific advancement we pursue.

We partner closely with the brightest minds in healthcare to ensure that every solution we create melds the latest technology with compassion and empathy. Because at Solventum, we never stop solving for you.

The Impact You'll Make in this Role:

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.

You Will Make an Impact By:

• 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.

Your Skills and Expertise

To set you up for success in this role from day one, Solventum requires (at a minimum) the following qualifications:

• 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

Additional qualifications that will help you succeed in the role:

• 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.

Work location:

• Remote

Travel: Relocation Assistance: Not authorized

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

Supporting Your Well-being

Solventum offers many programs to help you live your best life - both physically and financially. To ensure competitive pay and benefits, Solventum regularly benchmarks with other companies that are comparable in size and scope.

Onboarding Requirement: To improve the onboarding experience, you will have an opportunity to meet with your manager and other new employees as part of the Solventum new employee orientation. As a result, new employees hired for this position will be required to travel to a designated company location for on-site onboarding during their initial days of employment. Travel arrangements and related expenses will be coordinated and paid for by the company in accordance with its travel policy. Applies to new hires with a start date of October 1st 2025 or later.

Applicable to US Applicants Only:The expected compensation range for this position is $119,076 - $145,537, which includes base pay plus variable incentive pay, if eligible. This range represents a good faith estimate for this position. The specific compensation offered to a candidate may vary based on factors including, but not limited to, the candidate's relevant knowledge, training, skills, work location, and/or experience. In addition, this position may be eligible for a range of benefits (e.g., Medical, Dental & Vision, Health Savings Accounts, Health Care & Dependent Care Flexible Spending Accounts, Disability Benefits, Life Insurance, Voluntary Benefits, Paid Absences and Retirement Benefits, etc.). Additional information is available at: https://www.solventum.com/en-us/home/our-company/careers/#Total-Rewards

Responsibilities of this position include that corporate policies, procedures and security standards are complied with while performing assigned duties.

Solventum is committed to maintaining the highest standards of integrity and professionalism in our recruitment process. Applicants must remain alert to fraudulent job postings and recruitment schemes that falsely claim to represent Solventum and seek to exploit job seekers.

Please note that all email communications from Solventum regarding job o pportunities with the company will be from an email with a domain of @solventum.com. Be wary of unsolicited emails or messages regarding Solventum job opportunities from emails with other email domains.

Solventum is an equal opportunity employer. Solventum will not discriminate against any applicant for employment on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status.

Please note: your application may not be considered if you do not provide your education and work history, either by: 1) uploading a resume, or 2) entering the information into the application fields directly.

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