Machine Learning Engineer

Join us, and turn data into powerful financial insights!

Kraków – based opportunity with hybrid work model (2 days/week in the office).

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.

Your main 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

You’re ideal for this role if you have:

• 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

It is strong plus if you have:

• Familiarity with regulatory frameworks such as IFRS 9, ECL, or Basel III
• Hands-on experience with real-time or batch scoring pipeline integration
• Knowledge of Markov chains in the context of credit risk transitions
• Exposure to model monitoring and drift detection tools

#GETREADY  to meet with us!

We would like to meet you. If you are interested please apply and attach your CV in English or Polish, including a statement that you agree to our processing and storing of your personal data. You can always also apply by sending us an email at recruitment@itds.pl.

Internal number #7376