Source description
About the role
As a Specialized Analytics Senior Analyst at Citi, you will be a seasoned professional contributing to the development of new techniques and processes for Fraud Prevention within the Gen AI and Data Science area. Your role will involve integrating subject matter expertise to evaluate complex issues and provide impactful solutions. Your good analytical skills will be crucial in filtering, prioritizing, and validating dynamic material from multiple sources. Additionally, your excellent communication and diplomacy skills will be essential as you assume leadership roles within teams and coach new recruits. Responsibilities: - Design, develop, and deploy generative models (e.g., GPT, GAN, VAEs) for various applications. - Customize and fine-tune existing RAG frameworks or design recent RAG to meet project requirements. - Develop POC/full-scale solutions on various automations in Operations area, including Conversational AI and Multi-Agent Systems. - Collaborate with cross-functional teams to translate business requirements into AI solutions. - Advance the state-of-the-art in generative modeling through research and staying updated with the latest advancements. - Optimize models for performance, scalability, and robustness. - Implement and maintain AI pipelines and infrastructure for model training and deployment. - Mentor junior team members and provide technical guidance. - Write comprehensive documentation for models and algorithms. - Present findings and project progress to stakeholders and management. Recommended Qualifications: - Bachelor's or Master's degree in computer science, Data Science, Machine Learning, or a related field. A Ph.D. is a plus. - 8+ years of experience in machine learning and deep learning, focusing on generative AI solution design and development. - Proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or Keras. - Strong background in Prompt Engineering, building agentic AI, AI Agents, and large-scale automations in the banking domain. - Experience with natural language processing (NLP) and natural language generation (NLG). - Track record of deploying generative models in production environments using RAG frameworks. - Understanding of machine learning algorithms, data structures, and software engineering principles. - Strong problem-solving skills and the ability to work independently and collaboratively. - Excellent communication skills to explain technical concepts to non-technical stakeholders. The above job description provides an overview of the work performed as a Specialized Analytics Senior Analyst at Citi. Other job-related duties may also be assigned as required. As a Specialized Analytics Senior Analyst at Citi, you will be a seasoned professional contributing to the development of new techniques and processes for Fraud Prevention within the Gen AI and Data Science area. Your role will involve integrating subject matter expertise to evaluate complex issues and provide impactful solutions. Your good analytical skills will be crucial in filtering, prioritizing, and validating dynamic material from multiple sources. Additionally, your excellent communication and diplomacy skills will be essential as you assume leadership roles within teams and coach new recruits. Responsibilities: - Design, develop, and deploy generative models (e.g., GPT, GAN, VAEs) for various applications. - Customize and fine-tune existing RAG frameworks or design recent RAG to meet project requirements. - Develop POC/full-scale solutions on various automations in Operations area, including Conversational AI and Multi-Agent Systems. - Collaborate with cross-functional teams to translate business requirements into AI solutions. - Advance the state-of-the-art in generative modeling through research and staying updated with the latest advancements. - Optimize models for performance, scalability, and robustness. - Implement and maintain AI pipelines and infrastructure for model training and deployment. - Mentor junior team members and provide technical guidance. - Write comprehensive documentation for models and algorithms. - Present findings and project progress to stakeholders and management. Recommended Qualifications: - Bachelor's or Master's degree in computer science, Data Science, Machine Learning, or a related field. A Ph.D. is a plus. - 8+ years of experience in machine learning and deep learning, focusing on generative AI solution design and development. - Proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or Keras. - Strong background in Prompt Engineering, building agentic AI, AI Agents, and large-scale automations in the banking domain. - Experience with natural language processing (NLP) and natural language generation (NLG). - Track record of deploying generative models in production environments using RAG frameworks. - Understanding of machine learning algorithms, data structures, and software engineering principles. -