EY - GDS Consulting - AI and DATA - Gen AI - Gig

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Job Description: EY GDS Data and Analytics (D&A) Gig Senior Data Scientist

Role Overview: We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 3 7 years of experience in Data Science and Machine Learning preferably with experience in NLP Generative AI LLMs MLOps Optimization techniques and AI solution Architecture. In this role you will play a key role in the development and implementation of AI solutions leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cuttingedge AI models and systems. Additionally expertise in data engineering DevOps and MLOps practices will be valuable in this role.

Responsibilities:

Your technical responsibilities:

• Contribute to the design and implementation of stateoftheart AI solutions.
• Assist in the development and implementation of AI models and systems leveraging techniques such as Language Models (LLMs) and generative AI.
• Collaborate with stakeholders to identify business opportunities and define AI project goals.
• Stay updated with the latest advancements in generative AI techniques such as LLMs and evaluate their potential applications in solving enterprise challenges.
• Utilize generative AI techniques such as LLMs to develop innovative solutions for enterprise industry use cases.
• Integrate with relevant APIs and libraries such as Azure Open AI GPT models and Hugging Face Transformers to leverage pretrained models and enhance generative AI capabilities.
• Implement and optimize endtoend pipelines for generative AI projects ensuring seamless data processing and model deployment.
• Utilize vector databases such as Redis and NoSQL databases to efficiently handle largescale generative AI datasets and outputs.
• Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs.
• Collaborate with domain experts stakeholders and clients to understand specific business requirements and tailor generative AI solutions accordingly.
• Conduct research and evaluation of advanced AI techniques including transfer learning domain adaptation and model compression to enhance performance and efficiency.
• Establish evaluation metrics and methodologies to assess the quality coherence and relevance of generative AI outputs for enterprise industry use cases.
• Ensure compliance with data privacy security and ethical considerations in AI applications.
• Leverage data engineering skills to curate clean and preprocess largescale datasets for generative AI applications.

Requirements:

• Bachelors or Masters degree in Computer Science Engineering or a related field. A Ph.D. is a plus.
• Minimum 37 years of experience in Data Science and Machine Learning.
• Indepth knowledge of machine learning deep learning and generative AI techniques.
• Proficiency in programming languages such as Python R and frameworks like TensorFlow or PyTorch.
• Strong understanding of NLP techniques and frameworks such as BERT GPT or Transformer models.
• Familiarity with computer vision techniques for image recognition object detection or image generation.
• Experience with cloud platforms such as Azure AWS or GCP and deploying AI solutions in a cloud environment.
• Expertise in data engineering including data curation cleaning and preprocessing.
• Knowledge of trusted AI practices ensuring fairness transparency and accountability in AI models and systems.
• Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models.
• Excellent problemsolving and analytical skills with the ability to translate business requirements into technical solutions.
• Strong communication and interpersonal skills with the ability to collaborate effectively with stakeholders at various levels.
• Understanding of data privacy security and ethical considerations in AI applications.
• Track record of driving innovation and staying updated with the latest AI research and advancements.

Good to Have Skills:

• Apply trusted AI practices to ensure fairness transparency and accountability in AI models and systems.
• Utilize optimization tools and techniques including MIP (Mixed Integer Programming).
• Drive DevOps and MLOps practices covering continuous integration deployment and monitoring of AI models.
• Implement CI/CD pipelines for streamlined model deployment and scaling processes.
• Utilize tools such as Docker Kubernetes and Git to build and manage AI pipelines.
• Apply infrastructure as code (IaC) principles employing tools like Terraform or CloudFormation.
• Implement monitoring and logging tools to ensure AI model performance and reliability.
• Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment.
• Familiarity with DevOps and MLOps practices including continuous integration deployment and monitoring of AI models.

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