About the role
This role is a Data Science / AI Intern role focused on Credit Risk and Generative AI. It combines traditional data science and machine learning with modern LLM and RAG technologies in the banking/financial risk domain.
Requirements
Bachelor’s/Master’s student or recent graduate in Data Science, Computer Science, Mathematics, Statistics, Economics, Finance, or a related field;
Good understanding of Python and SQL;
Basic knowledge of statistics, probability, and Machine Learning;
Familiarity with Pandas, NumPy, Scikit-learn;
Understanding of LLM and Generative AI concepts;
Familiarity with RAG architecture and concepts such as embeddings, vector search, semantic retrieval, and prompt engineering;
Strong analytical and problem-solving skills;
Interest in Credit Risk, Banking, Data Science, AI, and GenAI.
Obligations
Support data preparation, cleaning, exploratory analysis, and feature engineering for credit risk models;
Assist in developing and evaluating statistical and Machine Learning models for credit risk assessment;
Explore and prototype LLM-based solutions for financial and risk-related use cases;
Develop and experiment with RAG (Retrieval-Augmented Generation) pipelines using internal documents, policies, procedures, and knowledge bases;
Work with document ingestion, chunking, embeddings, vector databases, retrieval, and LLM-based generation;
Evaluate the quality, relevance, factuality, and reliability of LLM/RAG outputs;
Support the development of AI assistants for credit risk analysis, policy/document search, and knowledge retrieval;
Perform data analysis to identify patterns, trends, and key credit risk drivers;
Support model performance monitoring, validation, and documentation;
Use Python and SQL for data analysis, modeling, and automation;
Collaborate with Risk, Data Science, AI, and Business teams to translate business requirements into analytical solutions;
Research new LLM, GenAI, and ML techniques and assess their applicability to Credit Risk.
Benefits
Opportunity to learn through hands-on experience in a professional environment;
Gain practical knowledge and real-world experience in data engineering;
Develop communication, collaboration, and problem-solving skills;
Improve teamwork abilities by working with cross-functional teams;
Receive guidance and support from experienced mentors;
Opportunity to build a successful career within Bir Ecosystem.
About us
Working at Bir ecosystem means creating value through technology, delivering meaningful impact to people, and building the solutions of tomorrow today.
Our teams operate through open dialogue, rapid decision-making, and a culture of continuous improvement. Our offices are places where ideas emerge, products take shape, and technology enables those ideas to become reality.
At Bir ecosystem, we positively impact the daily lives of millions of individuals and thousands of businesses through simple, reliable, and innovative solutions. The Fintech business (Birbank), Payments business (m10/MilliÖn), and E-commerce business (Birmarket) together form the country’s first fully integrated digital ecosystem.
Driven by the professionalism and expertise of our teams, the products we develop help shape new habits and contribute to the growth of the country’s digital culture.
Working here means growing within Bir ecosystem — an environment rich with opportunity. Diverse areas of expertise, multiple products, and continuous learning opportunities create the environment to unlock your potential and advance your career.
