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About This Role
The Data Scientist designs, develops, and deploys advanced analytics and machine learning models to improve healthcare outcomes and operational efficiency within healthcare SaaS platforms. This role collaborates with cross\-functional teams to analyze complex datasets, generate actionable insights, and integrate data\-driven solutions into secure, scalable, and compliant cloud\-native environments. The Data Scientist is responsible for driving innovation in statistical modeling, ensuring responsible AI practices, and supporting the adoption of modern data engineering and visualization best practices.
Key Responsibilities:
1\. Advanced Machine Learning \& AI Engineering
- Design, develop, and optimize supervised, unsupervised, and reinforcement learning models.
- Implement and fine\-tune deep learning architectures using frameworks such as TensorFlow and PyTorch.
- Apply ethical AI principles, including fairness, transparency, privacy, and bias mitigation.
- Deploy and monitor models in production environments, ensuring scalability and reliability.
2\. Data Engineering \& Cloud\-Native Architecture
- Build and maintain scalable data pipelines and ETL processes for real\-time and batch analytics.
- Engineer robust data architectures using Spark, MetaFlow, Databricks, and cloud platforms (Azure, AWS, GCP).
- Manage and manipulate large healthcare datasets for model development and analytics.
- Ensure data quality, integrity, and security throughout the analytics lifecycle.
3\. Statistical Modeling \& Quantitative Analysis
- Apply advanced statistical methods, hypothesis testing, and predictive analytics to healthcare data.
- Design and interpret causal AI experiments to support business and clinical decision\-making.
- Develop and validate predictive models for patient outcomes and operational efficiency.
4\. Data Visualization \& Communication
- Create compelling visualizations using Tableau, Power BI, D3\.js, or similar tools.
- Translate complex data and analytics into clear, actionable insights for technical and non\-technical stakeholders.
- Communicate findings effectively to engineering, product, and clinical teams.
5\. Healthcare Domain Expertise \& Compliance
- Ensure solutions adhere to healthcare data standards (HL7, FHIR) and regulations (HIPAA, GDPR, CCPA).
- Work with clinical datasets and understand healthcare workflows to ensure relevance and compliance.
- Stay current with healthcare regulations and data privacy requirements.
6\. Collaboration \& Continuous Learning
- Work closely with product, engineering, clinical, and compliance teams to deliver integrated, data\-driven solutions.
- Share knowledge and mentor team members on data science concepts and tools.
- Commit to continuous improvement and staying current with industry trends and best practices.
Required Qualifications:
*Education \& Experience Guidelines*
- Bachelor's degree in computer science, data science, or other relevant field.
- 5\-8 years of relevant work experience
- Experience developing predictive models and working with healthcare data standards.
- Occasional travel may be required.
Other Preferred Knowledge, Skills, Abilities or Certifications:
- Cloud Platforms: AWS, Azure, GCP
- AI Tools: Spark, MetaFlow, Databricks
- Healthcare Compliance: HIPAA, GDPR, CCPA
- Healthcare Standards: HL7, FHIR
- AI Ethics: Fairness, transparency, bias mitigation
- Certifications: Azure Data Scientist Associate, Google Cloud Data Engineer, CHDA, IBM Data Science
- Visualization Tools: Tableau, Power BI, d3\.js
- Communication: Ability to translate complex data into actionable insights
Fortive Corporation Overview
Fortive's essential technology makes the world safer and more productive. We accelerate transformation in high\-impact fields like workplace safety, build environments, and healthcare.
We are a global industrial technology innovator with a startup spirit. Our forward\-looking companies lead the way in healthcare sterilization, industrial safety, predictive maintenance, and other mission\-critical solutions. We're a force for progress, working alongside our customers and partners to solve challenges on a global scale, from workplace safety in the most demanding conditions to advanced technologies that help providers focus on exceptional patient care.
We are a diverse team 10,000 strong, united by a dynamic, inclusive culture and energized by limitless learning and growth. We use the proven Fortive Business System (FBS) to accelerate our positive impact.
At Fortive, we believe in you. We believe in your potential—your ability to learn, grow, and make a difference.
At Fortive, we believe in us. We believe in the power of people working together to solve problems no one could solve alone.
At Fortive, we believe in growth. We're honest about what's working and what isn't, and we never stop improving and innovating.
Fortive: For you, for us, for growth.
About Provation
Provation is a leading provider of healthcare software and SaaS solutions for clinical productivity, care coordination, quality reporting, and billing. Our purpose is to empower providers to deliver quality healthcare for all. Provation’s comprehensive portfolio spans the entire patient encounter, from pre\-procedure through post\-procedure, with solutions for physician and nursing documentation (Provation® MD, Provation® Apex, MD\-Reports, Provation® endoPRO®, and Provation® MultiCaregiver), anesthesia documentation (\#1 Best in KLAS Provation® iPro), patient engagement, surgical care coordination, quality reporting, and billing capture (Provation® SurgicalValet™), order set and care plan management (Provation® Order Set Advisor™ and Provation® Care Plans), and EHR embedded clinical documentation (Provation® Clinic Note). Provation has a loyal customer base, serving more than 5,000 hospitals, surgery centers, and medical offices, and 700 physician groups globally, including 19 of the top 20 U.S. hospitals. In 2021, Provation was acquired by Fortive Corporation, a Fortune 1000 company that builds essential technology and accelerates transformation in high\-impact fields like workplace safety, engineering, and healthcare. For more information about our solutions, visit provationmedical.com and follow us on Twitter, Facebook, and LinkedIn. Our purpose at Provation is to empower providers to deliver quality healthcare for all. To deliver on this commitment, we’re guided by our core values – Provation has a culture of CARES:Community \- We have a shared sense of improving healthcare, enriching the broader world we live in and serve. Accountability \- We own it and get it done with integrity. Respect \- We build diverse teams that collaborate and communicate with positive intent and trust. Excellence \- We welcome new ideas as we innovate quality solutions. Service \- We are passionate about putting customers first.
We Are an Equal Opportunity Employer. Fortive Corporation and all Fortive Companies are proud to be equal opportunity employers. We value and encourage diversity and solicit applications from all qualified applicants without regard to race, color, national origin, religion, sex, age, marital status, disability, veteran status, sexual orientation, gender identity or expression, or other characteristics protected by law. Fortive and all Fortive Companies are also committed to providing reasonable accommodations for applicants with disabilities. Individuals who need a reasonable accommodation because of a disability for any part of the employment application process, please contact us at applyassistance@fortive.com.
Bonus or Equity
This position is also eligible for equity as part of the total compensation package.
Pay Range
The salary range for this position (in local currency) is 137,200\.00 \- 229,100\.00
Provation is a leading provider of healthcare software and SaaS solutions for clinical productivity, care coordination, quality reporting, and billing. Our purpose is to empower providers to deliver quality healthcare for all. Provation’s comprehensive portfolio spans the entire patient encounter, from pre\-procedure through post\-procedure, with solutions for physician and nursing documentation (Provation® MD, Provation® Apex, MD\-Reports, Provation® endoPRO®, and Provation® MultiCaregiver), anesthesia documentation (\#1 Best in KLAS Provation® iPro), patient engagement, surgical care coordination, quality reporting, and billing capture (Provation® SurgicalValet™), order set and care plan management (Provation® Order Set Advisor™ and Provation® Care Plans), and EHR embedded clinical documentation (Provation® Clinic Note). Provation has a loyal customer base, serving more than 5,000 hospitals, surgery centers, and medical offices, and 700 physician groups globally, including 19 of the top 20 U.S. hospitals. In 2021, Provation was acquired by Fortive Corporation, a Fortune 1000 company that builds essential technology and accelerates transformation in high\-impact fields like workplace safety, engineering, and healthcare. For more information about our solutions, visit provationmedical.com and follow us on Twitter, Facebook, and LinkedIn. Our purpose at Provation is to empower providers to deliver quality healthcare for all. To deliver on this commitment, we’re guided by our core values – Provation has a culture of CARES:Community \- We have a shared sense of improving healthcare, enriching the broader world we live in and serve. Accountability \- We own it and get it done with integrity. Respect \- We build diverse teams that collaborate and communicate with positive intent and trust. Excellence \- We welcome new ideas as we innovate quality solutions. Service \- We are passionate about putting customers first.
We Are an Equal Opportunity Employer. Fortive Corporation and all Fortive Companies are proud to be equal opportunity employers. We value and encourage diversity and solicit applications from all qualified applicants without regard to race, color, national origin, religion, sex, age, marital status, disability, veteran status, sexual orientation, gender identity or expression, or other characteristics protected by law. Fortive and all Fortive Companies are also committed to providing reasonable accommodations for applicants with disabilities. Individuals who need a reasonable accommodation because of a disability for any part of the employment application process, please contact us at applyassistance@fortive.com.
The salary range for this position (in local currency) is 137,200\.00 \- 229,100\.00This position is also eligible for equity as part of the total compensation package.
Salary Context
This $137K-$229K range is above the median for Data Scientist roles in our dataset (median: $166K across 345 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 26,159 AI roles we're tracking, Data Scientist positions make up 2% of the market. At ProVation, 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 $204,700 based on 441 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300. This role's midpoint ($183K) sits 11% below the category median. Disclosed range: $137K to $229K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
ProVation AI Hiring
ProVation has 5 open AI roles right now. They're hiring across Data Scientist, AI Software Engineer. Positions span Remote, US, Kansas City, MO, US, Minneapolis, MN, US. Compensation range: $83K - $229K.
Remote Work Context
Remote AI roles pay a median of $156,000 across 1,221 positions. About 7% of all AI roles offer remote work.
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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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
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