Krakow, Lesser Poland, Poland
Live, first seen by us 43 days agoDesign, build and deploy AI/ML models for commercial, supply chain and manufacturing problems
Lead and contribute to data science projects from ideation through implementation
Apply best practices in feature engineering, model selection, validation and deployment
Translate complex data science concepts into insights for business partners
Review code and contribute to technical documentation
Design, build, and deploy AI/ML models that address business challenges in commercial operations, supply chain, manufacturing, and related domains.
Lead and contribute to data science projects from ideation through implementation
Apply best practices in data preparation, feature engineering, model selection, validation, and deployment.
Translate complex data science concepts into actionable insights for business partners
Participate in code reviews and contribute to technical documentation.
Required Qualifications & Skills - Education: Bachelor’s, Master’s, or PhD in Computer Science, AI, Data Science, Applied Mathematics, or related field. - Experience: direct AI/ML experience with demonstrated success building and deploying enterprise-grade solutions at scale.
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Day 43
Similar jobs usually come down between day 8 and day 60.
At GE Healthcare, jobs usually come down by about day 35.
From 11,783 similar postings that came down, and 49 of GE Healthcare’s. Coming down is not always a hire.
11 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- Relevant Expertise: Proven ability to apply advanced analytics and machine learning to solve real-world problems in areas such as forecasting, pricing, customer analytics, sales planning, computer vision, and operational optimization. - Technical Skills: Proficiency in ML algorithms, GenAI frameworks, and data engineering. Experience with Python, AWS, Azure, and open-source tools (R, SQL, Spark, TensorFlow, Keras, PyTorch, Scikit-learn). - MLOps & Engineering: Demonstrated ability to deploy, monitor, and maintain ML and GenAI models in production environments.
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Yes. We’ve followed 2 other Staff Data Scientist jobs there since April 2026. 2 came down, usually after about 33 days.
New Data Scientist postings at the employers we follow are down 4% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
GE HealthCare is accelerating its transformation through a series of strategic “Big Bets” in Commercial excellence, Logistics optimization, Inventory management, and Manufacturing innovation. The Enterprise AI team, part of the Chief Data and Analytics Office, is at the forefront of delivering robust, enterprise-grade AI and ML solutions that drive measurable business impact at scale.
As a Staff Data Scientist, you will play a key role in shaping and executing our AI strategy. You’ll collaborate across a unified, cross-functional delivery organization - partnering with experts in data engineering, ML engineering, analytics, GenAI development, and Corporate Finance - to solve complex business challenges and deliver scalable solutions.
Core Responsibilities
Required Qualifications & Skills
#LI-MT1
#LI-Hybrid
Placement within this range depends on:
Relevant skills and qualifications
Prior job-related experience
Internal equity considerations (alignment with colleagues in similar roles) e.t.c.
We review pay ranges regularly to ensure they remain competitive with the external market and align with our internal equity considerations.
Benefits & RewardsIn addition to base salary, our employees have access to a comprehensive package of benefits and allowances, which may include:
Health & wellness coverage
Retirement and or savings plans
Allowances or benefits to support role requirements (e.g., mobility, transport, or role-specific needs such as a company car or allowance where applicable)
Work-life balance support (e.g., flexible working, leave programs)
Recognition and incentive programs aligned with performance and company success
The exact benefits package depends on the role, location, and employment terms as specified in the Colleague Value Proposition document that will be shared prior to the interview or at the offer discussion stage.
Performance Bonus: Details to be shared during offer discussions
Relocation Assistance Provided: No
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Krakow, Lesser Poland, Poland
- Communication: Strong ability to convey complex technical concepts to non-technical stakeholders and senior executives. - Interpersonal Skills: Proven success working in cross-functional, hybrid, and virtual teams. - Ethics & Integrity: Commitment to ethical data science practices.
#LI-MT1 #LI-Hybrid Pay Range
No clear work-authorization passage found. Eligibility is unconfirmed.