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About This Role
You are collaborative, proactive, and motivated by solving complex, real world problems with AI. You thrive in fast‑paced, cross‑functional environments, balance innovation with delivery. Building production grade machine learning systems that have measurable clinical and business impact energizes you.
- Ability to Deliver Results: Proven success delivering AI solutions that improve operational efficiency, product quality, and user outcomes in regulated, high‑stakes environments.
- Comfort with Ambiguity: Strong ability to structure open‑ended problems, define success metrics, and make steady progress amid evolving requirements.
- Passion for Innovation: Deep interest in applied AI, computer vision, and emerging ML techniques, with a focus on translating research into reliable products.
- Positive Outlook: Consistently finds opportunities within technical, regulatory, and operational constraints.
- Strong Communication Skills: Able to clearly explain complex models and results to clinicians, engineers, product leaders, and executives.
- Bias for Action: Makes informed decisions quickly, prototypes rapidly, and iterates based on data and feedback.
What You Will Do
You will create and extend applied AI and ML solutions that enable intelligent, real\-time decisions in complex, regulated environments. You will collaborate with engineering, product, and domain experts to deliver reliable, scalable, and compliant ML solutions from concept through production.
- Execute end‑to‑end data science, from problem framing and data strategy to model development, deployment, and optimization.
- Design, train, and evaluate machine learning and deep learning models for real‑time and near‑real‑time inference.
- Apply techniques across computer vision, pattern recognition, predictive modeling, and generative AI to solve domain specific problems where accuracy, latency, and robustness are critical.
- Translate ambiguous domain and business requirements into clear methods, success metrics, and deployable systems.
- Build scalable data pipelines and feature engineering workflows using Python or statically compiled languages.
- Partner with engineering teams to integrate models into production systems with a focus on performance, reliability, and operational constraints.
- Implement monitoring, validation, and retraining strategies to manage drift and model performance.
- Use statistical methods and experimentation techniques to assess model quality, measure impact, and guide iterative improvements.
- Work within governance, privacy, and compliance requirements to ensure models meet organizational and regulatory standards.
- Evaluate emerging ML techniques and apply innovative approaches where they meaningfully improve outcomes.
- Improve code quality, testing, documentation, and reproducibility across data science and ML workflows.
- Communicate technical insights and recommendations effectively to both technical stakeholders and nontechnical decision makers.
This Opportunity Could Be for You If
- You hold a master’s degree in computer science, electrical or biomedical engineering, statistics, or a related field with a focus on machine learning or computer vision.
- Possess a fundamental understanding of linear algebra, quaternions, and 3D geometry.
- Possess a fundamental understanding of the operation and nuances of image sensors, lens optics, and the camera calibration process.
- Experience generating intrinsic and extrinsic camera matrices and estimating camera position and pose.
- Experience optimizing algorithms for embedded systems and servers.
- You have at least three years of experience as a data scientist, machine learning engineer, AI research engineer, or in an equivalent role.
- You have delivered data science projects from problem definition through production deployment.
- You are skilled at building ML models and working with large, complex datasets.
- You collaborate effectively with cross‑functional teams and translate requirements into solutions.
- You apply advanced statistical techniques to uncover patterns, trends, and strategic insights.
- You proactively check model performance and pursue continuous improvement.
- You stay current on developments in AI, machine learning, and data engineering and look for opportunities to introduce novel approaches.
Preferred Technical Qualifications
Candidates should show strength in the following areas:
- Experience designing, training, validating, and deploying deep learning models in production environments.
- Practical experience in the use of OpenCV, and PyTorch or TensorFlow.
- Strong background in computer vision, video analytics, or medical image analysis.
- Ability to build scalable data pipelines and labeling workflows using modern data engineering frameworks.
- Experience deploying models using cloud and edge infrastructure, with an understanding of latency and resource constraints.
- Solid grounding in statistical methods, experimentation design, time series analysis, and model evaluation.
- Familiarity with MLOps and DevOps practices, including CI/CD for ML, containerization, monitoring, and model lifecycle management.
- Production development in Python or statically compiled languages, and SQL for large scale analysis and model development.
- Experience working with regulated data and knowledge of healthcare privacy and medical device software standards is a plus.
- Effective communication skills and the ability to collaborate effectively with clinicians, engineers, product leaders, and regulatory partners.
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.
Pay Range
The salary range for this position (in local currency) is 109,700\.00 \- 183,200\.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 109,700\.00 \- 183,200\.00
Salary Context
This $109K-$183K range is below 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 ($146K) sits 28% below the category median. Disclosed range: $109K to $183K.
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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