EY - GDS Consulting - AI and DATA -...

Join EY GDS as a Senior Data Scientist on a Gig assignment in Chennai, India, and contribute to the Data and Analytics (D&A) team. We are looking for a skilled professional with 3-7 years of experience in Data Science and Machine Learning, with a preference for expertise in Natural Language Processing (NLP), Generative AI, Large Language Models (LLMs), MLOps, Optimization techniques, and AI solution architecture. You will be instrumental in developing and implementing cutting-edge AI solutions, leveraging your deep understanding of AI technologies and experience in designing and deploying advanced AI models and systems. Proficiency in data engineering, DevOps, and MLOps practices is highly valued.

Your responsibilities will include contributing to the design and implementation of state-of-the-art AI solutions, assisting in the development of AI models and systems using LLMs and generative AI, and collaborating with stakeholders to define project goals and identify business opportunities. You will stay abreast of the latest advancements in generative AI, evaluating their enterprise applications and developing innovative solutions. A key part of this role involves integrating with APIs and libraries like Azure OpenAI GPT models and Hugging Face Transformers, and implementing end-to-end pipelines for generative AI projects. You will utilize vector databases (e.g., Redis) and NoSQL databases for large-scale datasets and outputs, and implement similarity search algorithms. Collaboration with domain experts and clients will be crucial to tailor solutions. You will also conduct research on advanced AI techniques, establish evaluation metrics for generative AI outputs, and ensure compliance with data privacy, security, and ethical considerations. Data engineering skills for curating and preprocessing datasets are essential.

Required qualifications include a Bachelor's or Master's degree in Computer Science, Engineering, or a related field (a Ph.D. is a plus), with a minimum of 3-7 years of experience in Data Science and Machine Learning. You should possess in-depth knowledge of machine learning, deep learning, and generative AI techniques, with proficiency in Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks (e.g., BERT, GPT, Transformer models), familiarity with computer vision techniques, and experience with cloud platforms (Azure, AWS, GCP) are necessary. Expertise in data engineering, including data curation and cleaning, and knowledge of trusted AI practices are also required. Excellent problem-solving, analytical, communication, and interpersonal skills are vital for collaborating effectively with stakeholders and translating business requirements into technical solutions.

Good-to-have skills include applying trusted AI practices, utilizing optimization tools (e.g., MIP), driving DevOps and MLOps practices, implementing CI/CD pipelines, using tools like Docker, Kubernetes, and Git, applying infrastructure as code principles (e.g., Terraform), and implementing monitoring and logging tools. Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models, is also beneficial.