Responsible for designing, deploying and continuously optimizing scalable ML solutions
Engage in projects of the European Data Science & Advanced Analytics Team
Convert business requirements into operational KPIs and guide ML engineering decisions
Demonstrate flexibility to iteratively refine and adapt deployed ML solutions
Harmonize country-specific particularities with a unified, scalable ML architecture
Development and improvement of quality control methodologies, ML based imputation approaches and various projection methodologies
Support the full ML lifecycle including data exploration, feature engineering, model training, production deployment, validation and monitoring
Collaborate with engineering and operational teams to build robust ML models and pipelines
Ensure efficient and effective project delivery to meet project team and client expectations

Degree in Computer Science, Statistics, Mathematics, Engineering or a related quantitative field
Substantial experience delivering production-grade ML solutions, preferably in regulated or data intensive domains (e.g., healthcare, life sciences, market analytics)
Strong Python expertise for data and ML engineering, including modern data processing frameworks (e.g., Pandas, Polars, NumPy) and scalable ML tooling
Hands-on experience with cloud-native ML environments (AWS, Azure or GCP), including containerization and deployment best practices
Deep understanding of ML fundamentals, including model selection, validation strategies, performance optimization and monitoring in production
Strong analytical mindset with high standards for data quality, reproducibility, and robustness
Proven ability to work autonomously while collaborating effectively across cross-functional and international teams
Strong ownership mentality, with effective prioritization and time-management skills in fast-paced, evolving environments
Excellent communication skills, with the ability to translate complex technical concepts into clear insights.

Senior Data Scientist

Key skills