General duties
- Develop, deploy, and maintain production-grade ML models for business-critical use cases including Next Best Offer/Action, pricing optimization, anti-fraud detection, and AML (Anti-Money Laundering) models.
- Own the end-to-end ML lifecycle: problem framing, data exploration, feature engineering, model training and validation, deployment, monitoring, and continuous improvement.
- Design and implement robust model monitoring and retraining pipelines to ensure model performance over time.
- Collaborate with Data Engineers and Software Engineers to integrate ML models into production systems and streaming/batch pipelines.
- Contribute to the design and improvement of the in-house ML platform to enhance productivity and model deployment efficiency.
- Work with stakeholders across the bank to understand business requirements and translate them into ML solutions.
- Ensure models meet governance, compliance, and audit requirements; maintain documentation and model cards.
Requirements
Must have
- 3+ years of hands-on experience in ML engineering or data science roles.
- Strong foundation in mathematics, statistics, ML algorithms, metrics, and loss functions.
- Advanced expertise in Python and ML ecosystem (NumPy, pandas, scikit-learn).
- Strong SQL skills for data manipulation and analysis.
- Verbal and written English at Upper Intermediate level (B2+) or above.
Nice to have
- Proven track record of deploying models to production.
- Experience with gradient boosting libraries (XGBoost, CatBoost, LightGBM).
- Spark skills, including complex joins, subqueries, CTEs, window functions, and large-scale data processing.
- Experience with ML lifecycle tools such as MLflow, Azure Databricks, or similar platforms.
- Proficiency in writing clean, efficient, scalable, and maintainable Python code.
- Experience with model deployment, monitoring, and MLOps best practices.
- Understanding of model validation, A/B testing, and evaluation metrics.
- Experience with LLM-based applications or agentic AI frameworks (LangChain, LangGraph).
- Familiarity with deep learning frameworks (PyTorch, TensorFlow, Keras).
- Experience with workflow orchestration tools (Airflow, Prefect).
- Knowledge of real-time model serving and streaming ML pipelines.
- Experience in banking, fintech, or highly regulated industries.
- Familiarity with Azure cloud services and Kubernetes.
DSK Bank offers
- Excellent opportunities for professional and career development in one of Bulgaria's leading banks;
- Food vouchers in the amount of 102.26 EUR per month;
- 25 paid holiday leave;
- Additional Health Insurance;
- Favorable conditions for housing and mortgage lending, as well as for bank products and services;
- Annual bonus scheme depending on the achieved results;
- Preferential conditions for Multisport / CoolFit card;
- Great location;
- Discounts in various companies;
- Professional trainings for specific knowledge and skills (internal academies);
- Refer a Friend Bonus.
Documents for application
CV
