Requirements: English
Company: ABB Business Services
Region: Krakw , Lesser Poland Voivodeship
technologies-expected :
- Python
- SQL
- KQL
- Azure
- AWS
- Kubernetes
about-project :
- We are seeking a Data Scientist/AI Modeling Engineer to lead the design and implementation of advanced probabilistic and statistical models for risk assessment and asset management of industrial equipment. This role involves developing models to optimize maintenance strategies through predictive maintenance analytics, optimization modeling, and AI-driven insights. The primary objective is to help clients minimize downtime, enhance asset reliability, and improve operational efficiency.
- You will be responsible for working with large-scale structured and unstructured datasets leveraging cutting-edge data science techniques to improve data quality and drive strategic, data-informed decision-making.
responsibilities :
- Develop and maintain probabilistic and statistical models to evaluate and mitigate risks associated with industrial assets and operations
- Apply reliability theory and operational research methodologies to optimize maintenance strategies through predictive maintenance analytics, optimization modeling, and AI-driven insights
- Implement advanced optimization techniques to analyze complex datasets, providing actionable insights for decision-making and process improvements
- Extract, transform, and integrate data from diverse structured and unstructured sources to support robust model development
- Collaborate with engineering teams to transition models from development to pro-duction and continuously monitor and refine models performance
- Document processes and findings, creating reports and presentations to communicate insights to stakeholders
requirements-expected :
- Advanced degree in Applied Science, (Industrial/Reliability/Mechanical) Engineering, Data Science or a related field. (Masters preferred)
- Proven expertise (preferrable 3+ years) in data science and analytics for key areas (such as probability and statistics, time-series analysis, pattern recognition, optimization, and predictive modeling) for predictive maintenance and risk assessment in industrial settings
- Preferred knowledge in reliability engineering and operational research methodologies
- Proficiency in Python, or similar, and experience with data processing frameworks
- Experience with query languages (SQL, KQL, etc.), cloud environments (Azure, AWS, etc.) and modern software development tools and processes (source control with git, unit/integration tests, CI/CD, serverless deployment with Kubernetes)
benefits :
- sharing the costs of sports activities
- private medical care
- sharing the costs of foreign language classes
- sharing the costs of professional training & courses
- life insurance
- remote work opportunities
- flexible working time
- corporate products and services at discounted prices
- integration events
- corporate sports team
- saving & investment scheme
- corporate library
- coffee / tea
- sharing the commuting costs
- employee referral program
- charity initiatives
- family picnics