Interested in this Data Scientist role at Solventum?
Apply Now →Skills & Technologies
About This Role
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:
Job DescriptionJob Title \- Data Scientist
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.*
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. Here, you will make an impact by:
How you will make an 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.
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 could help you succeed even further in this role include:
- 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
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 $124,000 \- $170,500, 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 opportunities 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.
Please note, Solventum does not expect candidates in this position to perform work in the unincorporated areas of Los Angeles County.
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.
Solventum Global Terms of Use and Privacy Statement
Carefully read these Terms of Use before using this website. Your access to and use of this website and application for a job at Solventum are conditioned on your acceptance and compliance with these terms.
Please access the linked document by clicking here. Before submitting your application you will be asked to confirm your agreement with the
terms.
Salary Context
This $124K-$170K range is below the median for Data Scientist roles in our dataset (median: $157K across 236 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 3,823 AI roles we're tracking, Data Scientist positions make up 8% of the market. At Solventum, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $198,000 based on 808 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($147K) sits 26% below the category median. Disclosed range: $124K to $170K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Solventum AI Hiring
Solventum has 5 open AI roles right now. They're hiring across AI/ML Engineer, MLOps Engineer, Data Scientist. Positions span UT, US, Remote, US, Pittsburgh, PA, US. Compensation range: $114K - $196K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 median).
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.