Data Scientist

We are looking for a Data Scientist to help design and build intelligent, model-driven solutions across the Bank Group. In this role, you will develop and deploy machine learning models that drive customer understanding and business decisions, work closely with business stakeholders to translate complex analytical challenges into end-to-end ML solutions, and contribute to the evolution of our data science capabilities.

What You’ll Do

Design, develop, and deploy machine learning models focused on customer behavioral analytics, including churn prediction, NBA/NBO (next best action/offer), customer segmentation, and cLTV (customer lifetime value) estimation
Build end-to-end ML solutions – from data exploration and feature engineering through model training, validation, and production deployment
Apply and evaluate a broad range of ML algorithms for classification and regression tasks, selecting approaches appropriate to the business problem and data characteristics
Define, monitor, and communicate model performance using relevant ML metrics, ensuring solutions remain reliable over time
Collaborate with data engineers, analysts, and business stakeholders to identify opportunities for ML-driven improvements and translate them into actionable insights
Prepare and maintain documentation for models, experiments, and analytical methodologies to support reproducibility and knowledge sharing
Contribute to the strategic development of the Bank Group’s data science platform and ML capabilities

What We Expect

Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Econometrics, Computer Science, or a related field
At least 2 years of experience as a Data Scientist, Decision Scientist, or in a similar role
Strong SQL and Python programming skills, including experience with data manipulation & ML libraries (pandas, numpy, scikit-learn, XGBoost, LightGBM)
Hands-on experience applying ML algorithms for classification and regression problems
Strong understanding of core ML metrics and model evaluation techniques
Experience building end-to-end ML pipelines, including feature engineering, model training, and deployment
Strong analytical thinking and problem-solving skills with attention to detail
Ability to work independently and deliver high-quality solutions
Professional proficiency in English, both written and spoken

Nice to have

Experience with ML on Azure (Azure Machine Learning, Azure Databricks)
Familiarity with Azure, GCP, or AWS data stack and cloud-based ML workflows
Experience with MLflow or similar experiment tracking and model registry tools
Knowledge of model monitoring, drift detection, and retraining strategies
Experience working with modern data warehousing environments (e.g. Snowflake, BigQuery, Synapse)
Familiarity with software engineering best practices including version control, CI/CD, and testing

What We Offer

Opportunity to work on large-scale data and analytics initiatives within a leading financial institution
Participation in strategic projects with tangible business impact
Collaborative and supportive team environment
Opportunities for professional growth and continuous learning

Monthly Salary:

3780 - 5670 Eur. gross

Data Scientist

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