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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and deploying predictive models using Python and machine learning techniques, with a strong focus on process optimization and predictive maintenance in heavy manufacturing industries. Proficient in communicating complex analytical findings to stakeholders in both English and Polish.
Highest-signal resume keywords
Python Data Science LibrariesMachine Learning in ManufacturingAnomaly DetectionTime-Series Feature EngineeringFluent English and Polish
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Predictive ModelingMachine LearningProcess OptimizationScrap ReductionProduct Quality PredictionAsset Health MonitoringGradient BoostingClassical Machine LearningTime-Series AnalysisFeature Engineering
Soft Skills
Clear CommunicationProblem TranslationStakeholder Engagement
Tools & Technologies
LightGBMXGBoostCatBoostScikit-LearnPandasPolarsNumPySciPySCADATelemetry
Certifications & Qualifications
Advanced Degrees in Data ScienceMachine Learning Certifications
Industry Keywords
Heavy ManufacturingContinuous ManufacturingPulp and PaperSteelChemicalsRefiningGlassPharmaceuticals
Tech Stack
Tools & technologiesCloudNumpyPandasPythonScikit-Learn
About the role
Key responsibilities & impact- Develop and deploy predictive models using Python and practical machine learning techniques
- Work with production, process, sensor, and time-series data to derive actionable insights
- Optimize processes and support quality and scrap prediction
- Develop solutions for anomaly detection and predictive maintenance
- Independently own analytics and modeling work
- Ensure high-quality deliverables
- Communicate findings and recommendations clearly to customer stakeholders in professional English
Requirements
What you’ll need- Proven experience applying machine learning to heavy/continuous manufacturing industries, such as pulp and paper, steel/metals, chemicals, refining, glass, or pharmaceuticals
- Experience with high-frequency, noisy historian/SCADA/telemetry feeds
- Experience handling sensor drift and missing data
- Experience with continuous time-series feature engineering
- Hands-on experience developing and deploying models for at least two of: scrap reduction and product quality prediction; process parameter optimization and yield maximization; asset health, anomaly detection, or predictive maintenance
- Mastery of Python data science libraries including pandas, polars, numpy, scipy
- Mastery of classical machine learning and gradient boosting tools including LightGBM, XGBoost, CatBoost, and scikit-learn
- Experience with time-series packages
- Ability to translate ambiguous operational problems into structured analytical tasks
- Ability to work directly with plant engineers and operations stakeholders
- Ability to present findings clearly
- Willingness to travel to the UK approximately twice during the initial project phase
- Fluent English and Polish
- Additional programming languages or data science tools are nice to have
- Familiarity with cloud platforms and data science or machine learning services is nice to have
- Advanced degrees or certifications in Data Science, Machine Learning, or related fields are nice to have
Benefits
Comp & perks- A cafeteria system allowing employees to personalize benefits
- Referral bonuses of up to PLN6,000
- Additional revenue-sharing opportunities for initiating partnerships with new clients
- Dedicated Team Manager guidance
- Tailored technical mentoring from an assigned technical leader
- Team-building budget for online and on-site team events
- Opportunities to participate in charitable initiatives and local sports programs
- Supportive and inclusive work culture emphasizing diversity and mutual respect
- Fully funded training, certifications, and participation in technology conferences
- Remote work for candidates based in Poland