З/п не указана
Требуются навыки Python и Data Engineering для сбора, обработки данных и разработки AI решений
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Стажёр по искусственному интеллекту и анализу рисков
в Bir
О роли
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.
Vəzifə öhdəlikləri
- 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.
Tələblər
- 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.
Üstünlüklər
- 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.
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.
Vəzifə öhdəlikləri
- 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.
Tələblər
- 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.
Üstünlüklər
- 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.
Локация
Bakı
Опыт
Junior
Занятость
Полная занятость
Зарплата
Не указана
Опубликовано
25 августа 2026
Дедлайн
24 сентября 2026
О компании
Bir
Technology · 5,001-10,000 · Baku
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