Data Scientist & Machine Learning Engineer

Quick Facts

• Role: IT Architect / Data Scientist (Machine Learning & Data Science)
• Work mode: Hybrid (1 day per month at the client office in Warsaw)

Description

You will design and develop machine learning and data science solutions, including preparing, processing, and analyzing large datasets. You will build and evolve ML models—particularly anomaly detection—and work on how they are deployed and maintained in production using MLOps practices. You’ll also support technical architecture and the integration of ML solutions with the rest of the IT environment.

Responsibilities

• Design and develop Machine Learning and Data Science solutions
• Build data pipelines: preparation, processing, and analysis of large datasets
• Implement feature engineering processes
• Build and evolve ML models, including anomaly detection solutions
• Design deployment and maintenance approach for production models following MLOps practices
• Containerize and deploy solutions with Docker and Kubernetes
• Co-create technical architecture for developed solutions
• Ensure code quality, testability, and compliance with software best practices
• Collaborate with engineering teams to integrate ML solutions with other IT components

Requirements

• 4+ years of programming experience in Python
• Very good knowledge of Machine Learning
• Practical experience with scikit-learn, pandas, and XGBoost
• Experience with anomaly detection solutions
• Experience with data preparation, processing, and analysis
• Practical knowledge of feature engineering
• Good knowledge of SQL
• Knowledge and experience with MLOps
• Experience with Docker and Kubernetes
• Good knowledge of Linux
• Knowledge of software development best practices, QA, and software quality processes
• Very good analytical skills
• Creativity, independence, and ability to search for and propose optimal solutions

Benefits

• Professional and personal development support
• Individual support from a Service Delivery Manager to plan a career path and ensure comfort and satisfaction
• Training, certificates, and conferences—co-funded or fully covered
• SmartChange: opportunity to change projects based on your preferences
• Work-life balance initiatives: integration events, sports activities, and edge1talks webinars
• Physical activity support: sports initiatives and training room rentals
• Health package: private care, sports card, insurance, and a psychological support platform
• Flexible benefits: you choose how to spend benefit points