Junior Data Modeler
HybridSofia, Sofia-Capital, Bulgaria
Job Summary
Analyse large datasets to identify patterns, trends, and risk drivers that help clients make better lending and customer decisions. Prepare and transform data for modelling, ensuring accuracy, quality, and consistency throughout the process. Monitor and validate model performance, investigating issues and implementing improvements where needed. Use GenAI and other analytical tools to improve efficiency, automate routine tasks, and enhance analytical insights. Apply a continuous improvement mindset by identifying data issues, process inefficiencies, and inconsistencies, and recommending practical solutions. Work with other teams and clients to understand requirements and provide analytical solutions that meet their needs. Follow modelling, governance, and quality standards to ensure reliable and robust analytical outputs.
Required Qualifications
- University degree with a high numerical content (such as Mathematics, Statistics, Computer Science, Economics)
- Knowledge in statistical software packages and other related technologies
- Fluent English – written and spoken
- Working knowledge in Python – preferably both Python's own syntax but also some of its main analytical packages (such as Pandas, Numpy, scikit-learn)
- Understanding of how and when to apply analytical approaches including regression analysis and machine learning
- Grasp of probability, statistical inference, optimization algorithms, linear algebra, and calculus
Desired Qualifications
- experience with BI Tools such as Tableau and Power BI
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