Internship AI Engineer

As an Internship AI Engineer in the Advanced Analytics Global area, you will contribute to the development and deployment of AI solutions that support decision-making processes for clients in banking, finance, insurance, utilities, and corporate sectors. Your responsibilities will include: Model Development: Assist in designing, implementing, and testing machine learning and deep learning models for predictive analytics, risk assessment, and customer behavior analysis. Data Processing: Work with large datasets to perform data cleaning, feature engineering, and exploratory data analysis to ensure data quality and relevance for modeling. Algorithm Optimization: Collaborate with senior engineers to optimize algorithms for performance, scalability, and accuracy, including hyperparameter tuning and model validation. Prototyping: Develop proof-of-concept prototypes to demonstrate the feasibility and business value of new AI approaches. Documentation: Maintain clear documentation of methodologies, code, and experimental results to support knowledge sharing and reproducibility. Cross-functional Collaboration: Work closely with data scientists, software engineers, and business analysts to integrate AI solutions into existing systems and workflows. Research: Stay updated on the latest AI trends and technologies, and propose innovative solutions to enhance the Advanced Analytics Global center of excellence. Testing and Validation: Conduct rigorous testing of models using appropriate metrics and validation techniques to ensure robustness and reliability in production environments. Tool Utilization: Use tools and frameworks such as Python, TensorFlow, PyTorch, scikit-learn, and cloud platforms (e.g., AWS, Azure) for model development and deployment. Reporting: Present findings and progress to team members and stakeholders through reports and presentations.

To be successful in this role, you should have: - Currently pursuing a degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, Statistics, or a related field. - Strong programming skills in Python, with experience in libraries such as NumPy, Pandas, and scikit-learn. - Basic understanding of machine learning algorithms (e.g., regression, classification, clustering, neural networks). - Familiarity with deep learning frameworks like TensorFlow or PyTorch. - Experience with data manipulation and analysis using SQL or similar query languages. - Knowledge of version control systems (e.g., Git). - Excellent problem-solving and analytical skills. - Strong communication skills in English; Italian is a plus. - Ability to work independently and as part of a team in a fast-paced environment. - Prior internship or project experience in AI/ML is preferred but not required.

CRIF是一家欧洲信用评级机构，专注于为非金融企业提供信用评级服务，并获得欧洲证券和市场管理局（ESMA）授权。