Junior Data Scientist

Posted 12 Days Ago
Be an Early Applicant
თბილისი
In-Office
Junior
Fintech • Financial Services
The Role
Supports model validation, performance monitoring, back-testing, benchmark and challenger model development, model risk assessment, and risk mitigation recommendations. Prepares validation reports, contributes to model governance, and helps automate validation and monitoring processes. The role requires foundational statistical modeling and machine learning knowledge, structured data experience, Python or R, SQL, and clear communication skills. Work is conducted with guidance from senior team members.
Summary Generated by Built In

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. Members of the team are testing, validating, challenging and monitoring all the AI/ML models and solutions developed/used in the bank in order to mitigate model risk and create safe environment for operations in different areas of business (credit risk, marketing, customer care, optimization of back office operations, etc.). We are looking for people interested to explore business insights, with foundational knowledge in model development and validation eager to learn how to identify, assess and mitigate model risks. If you are a resourceful, goal-oriented person enjoying collaboration to deliver solutions, this may be an opportunity for you 

  

Key Responsibilities: 

All responsibilities below are carried out within a structured team environment, with guidance and oversight from senior team members. 

  • 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. 

Preferred Qualifications: 

  • 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. 

  • 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. 

  • Solid foundational knowledge of statistical modeling and machine learning concepts. 

  • 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. 

  • Proficiency in Python and/or R; working knowledge of SQL for data manipulation and analysis. 

  • 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. 


Knowledge, Skills and Abilities: 

  • 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. 



Interested candidates, please fill in the information, attach your CV and submit by clicking “apply for position now”. Deadline is October 30 2026.


Skills Required

  • Degree in Statistics, Mathematics, Data Science, Computer Science, or a related field
  • 0–1 year of relevant work experience, or equivalent academic, internship, or personal project experience
  • Experience working with structured datasets
  • 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 communicate analytical insights to technical and non-technical audiences
  • Strong analytical and problem-solving skills
  • Critical thinking and attention to detail
  • Ability to troubleshoot issues methodically and escalate appropriately
  • Proficiency in written Georgian and English
  • Familiarity with deep learning, reinforcement learning, or natural language processing
  • Familiarity with Large Language Models and practical applications
  • Exposure to prompt engineering, fine-tuning, or LLM evaluation
  • Basic understanding of transformer architecture and attention mechanisms
  • Awareness of Retrieval-Augmented Generation systems, vector databases, embedding models, and document retrieval pipelines
  • Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn
  • Familiarity with Big Data technologies such as Hadoop, Hive, Spark, or NoSQL
  • Knowledge of data visualization libraries or tools such as Matplotlib, Plotly, Power BI, or Tableau
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The Company
4,854 Employees

What We Do

JSC Bank of Georgia is a leading universal bank in Georgia, providing a comprehensive range of financial services including retail, corporate, and investment banking. It focuses on digital banking, loan portfolios, and financial inclusion, serving both individual and business clients. The bank is a major financial institution in the region, known for its strong market position and commitment to providing customer-centric digital experiences and financial tools to support economic growth.

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