Data scientist in model risk

Model Risk Management Department at Bank of Georgia is looking for passionate, curious, and talented Junior Data Scientist to join our growing team . You will have an opportunity to contribute to various innovative data-driven products and scalable intelligent systems.

• Conduct model validations and assess model performance, conceptual soundness, input data quality, and development methodology.
• Carry out model outcomes analysis, including back-testing exercises.
• Evaluate new and existing models' overall fit and suitability with their intended use and purpose.
• Identify models' key assumptions, limitations, and weaknesses, assess the effectiveness of compensating controls, and contribute to practical risk mitigation recommendations.
• Develop benchmark and challenger models to support the assessment of models under review.
• Prepare clear, well-structured validation reports and present findings and observations to the immediate team.
• Develop familiarity with the Model Risk Policy and apply relevant requirements in day-to-day work.
• Monitor model performance to support early and proactive identification of model risks.
• Support model governance activities and contribute to the optimization of the validation and monitoring process through automation, incorporating regulatory changes and other initiatives.

• Degree in Statistics, Mathematics, Data Science, Computer Science, or a related field.
• 0–1 year of relevant working experience; a strong academic background, internship experience, or a portfolio of personal and academic projects is acceptable in lieu of professional experience.
• Solid foundational knowledge of statistical modeling and machine learning concepts.
• Proficiency in Python and/or R; working knowledge of SQL for data manipulation and analysis.
• Knowledge of relational database concepts and data modeling.
• Foundational data visualization and storytelling skills; ability to build basic dashboards using visualization tools, with guidance.
• Ability to communicate analytical insights using data to both technical and non-technical audiences.
• Strong analytical and problem-solving skills.
• Critical thinking and attention to detail.
• Team player and self-starter, with a desire to learn and add value, and a can-do attitude.
• Ability to troubleshoot issues methodically and escalate to senior colleagues where appropriate.
• Receptiveness to feedback and mentorship as part of ongoing professional development.
• Proficiency in writing clearly and concisely in both Georgian and English.
• Будет плюсом: Experience in the financial sector, particularly banking, is an advantage but is not required; Exposure to working with structured datasets; experience with complex or large-scale data is a plus; Familiarity with deep learning, reinforcement learning, or natural language processing is an advantage; Familiarity with Large Language Models (LLMs) and their practical applications; exposure to prompt engineering, fine-tuning, or LLM evaluation is a plus; Basic understanding of transformer architecture and attention mechanisms; hands-on experience with transformer-based models through academic or personal projects is an advantage; Awareness of Retrieval-Augmented Generation (RAG) systems and their components, including vector databases, embedding models, and document retrieval pipelines, is a plus; Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-Learn, etc.) and Big Data technologies (Hadoop/Hive, Spark, NoSQL, etc.) is a plus; Knowledge of data visualization libraries (such as Matplotlib or Plotly) and tools (such as Microsoft Power BI or Tableau) is a plus

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