As a Machine Learning Engineer, you will be working for our client, a global financial institution focused on innovation in credit risk analytics. You will be contributing to a high-impact project aimed at enhancing predictive modeling capabilities for consumer and corporate lending portfolios. The client is investing in state-of-the-art techniques to assess risk, improve compliance, and streamline loan evaluation processes. You will collaborate with cross-functional teams to build, validate, and deploy robust models that drive data-informed decisions across the organization.
Join us, and turn data into powerful financial insights!
Kraków - based opportunity with hybrid work model (2 days/week in the office).
responsibilities :
Developing predictive models for credit scoring, loan deterioration, and time-to-default
Performing data exploration and feature engineering using behavioral and transactional credit data
Ensuring model performance, robustness, and interpretability using statistical and ML-based metrics
Collaborating with Data Engineering teams to integrate models into production environments
Supporting the documentation, audit, and validation processes for regulatory compliance
Applying advanced ML techniques such as XGBoost, LightGBM, and survival models to risk problems
Monitoring and retraining models to ensure long-term reliability and compliance
Presenting findings and explaining model logic to risk, compliance, and audit stakeholders
requirements-expected :
3+ years of experience in a Data Scientist or ML Engineer role in a regulated or financial environment
Proven experience with credit risk modeling including logistic regression, scorecards, and survival models
Strong coding skills in Python and experience with libraries such as scikit-learn, XGBoost, pandas, SHAP
Proficiency in SQL for data extraction, transformation, and analysis
Understanding of statistical concepts and model evaluation techniques
Familiarity with credit lifecycle data including payments, delinquencies, and account activity
Experience with model interpretability tools and practices
Ability to work collaboratively with engineering and risk teams
Strong communication skills with the ability to simplify complex model logic for non-technical stakeholders
Experience working in environments that require model documentation and validation
offered :
Stable and long-term cooperation with very good conditions
Enhance your skills and develop your expertise in the financial industry
Work on the most strategic projects available in the market
Define your career roadmap and develop yourself in the best and fastest possible way by delivering strategic projects for different clients of ITDS over several years
Participate in Social Events, training, and work in an international environment
