EH-FY25-Consulting-AI & Data-Consultant-Data Scientist-ODC

Strategy & Analytics AI & Data In this age of disruption, organizations need to navigate the future with confidence, embracing decision making with clear, data-driven choices that deliver enterprise value in a dynamic business environment. The AI & Data team leverages the power of data, analytics, robotics, science and cognitive technologies to uncover hidden relationships from vast troves of data, generate insights, and inform decision-making. Together with the Strategy practice, our Strategy & Analytics portfolio helps clients transform their business by architecting organizational intelligence programs and differentiated strategies to win in their chosen markets. AI & Data will work with our clients to: - Implement large-scale data ecosystems including data management, governance and the integration of structured and unstructured data to generate insights leveraging cloud-based platforms - Leverage automation, cognitive and science-based techniques to manage data, predict scenarios and prescribe actions - Drive operational efficiency by maintaining their data ecosystems, sourcing analytics expertise and providing As-a-Service offerings for continuous insights and improvements Job Summary: We're seeking a highly skilled Generative AI Engineer to design, develop, and implement generative AI models and systems for financial applications. This role requires a deep understanding of LLMs, RAG, machine learning, natural language processing (NLP), and neural networks. The ideal candidate will have experience with state-of-the-art generative models such as GPT, GANs, and VAEs, and will be able to apply these technologies to real-world financial problems. Key Responsibilities: Generative AI Model Development: Design and develop generative AI models for various financial applications, including text generation, image synthesis, and data augmentation. Knowledge on RAG implementation, prompt engineering and validating LLM output is required. Collaboration: Collaborate with cross-functional teams to identify opportunities for applying generative AI solutions in finance, such as risk management, portfolio optimization, and financial forecasting. Research and Development: Conduct research and stay up-to-date with the latest advancements in generative AI and machine learning, applying this knowledge to financial problems. Model Implementation and Optimization: Implement and optimize generative models using frameworks such as TensorFlow, PyTorch, and Hugging Face, ensuring high performance and accuracy. Model Evaluation and Fine-Tuning: Evaluate and fine-tune models to ensure high performance and accuracy, using metrics relevant to financial applications. Documentation and Knowledge Sharing: Develop and maintain documentation for AI models and systems, and provide technical guidance and mentorship to junior team members. Stakeholder Communication: Present findings and project updates to stakeholders and senior management, communicating complex technical concepts effectively. Financial Modeling: Develop and apply ML models to predict stock prices, forecast revenue, and estimate credit risk, using generative AI models to generate synthetic financial data. Risk Analysis: Identify and mitigate potential risks in financial portfolios using ML-powered risk assessment tools. Technical Skills: Proficiency in programming languages like Python, R, or MATLAB. Experience with ML libraries like scikit-learn, TensorFlow, or PyTorch. Familiarity with deep learning and generative models, including GPT, GANs, and VAEs. Knowledge of financial markets, instruments, and regulations.

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