Computer Vision Data Scientist at Fortive

Minneapolis, Minnesota, United States -

Full Time

Start Date

Immediate

Expiry Date

18 Jun, 26

Salary

0.0

Posted On

20 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Computer Vision, Machine Learning, Deep Learning, AI, Data Science, Model Development, Deployment, Optimization, Python, Generative AI, Pattern Recognition, Statistical Methods, Experimentation, MLOps, PyTorch, TensorFlow

Industry

electrical;Appliances;and Electronics Manufacturing

Description

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 stronger, safer, and smarter. We accelerate transformation across a broad range of applications including environmental, health and safety compliance, industrial condition monitoring, next-generation product design, and healthcare safety solutions. We are a global industrial technology innovator with a startup spirit. Our forward-looking companies lead the way in software-powered workflow solutions, data-driven intelligence, AI-powered automation, and other disruptive technologies. 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 groundbreaking sustainability solutions. We are a diverse team 18,000 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.

Responsibilities

The role involves creating and extending applied AI and ML solutions to enable intelligent, real-time decisions in complex, regulated environments, collaborating with cross-functional teams to deliver reliable, scalable, and compliant ML solutions from concept through production. Responsibilities include executing end-to-end data science, designing and training deep learning models, building scalable data pipelines, and implementing monitoring and validation strategies.