EY seeks a Senior Data Scientist to join our team. In this role, you will be instrumental in developing and implementing advanced AI solutions, leveraging your expertise in generative AI and machine learning to solve complex enterprise challenges.
What You'll Do
- Contribute to the design and implementation of state-of-the-art AI solutions for enterprise use cases.
- Develop and implement 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 advancements in generative AI and evaluate their potential applications for enterprise challenges.
- Integrate with APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models.
- Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment.
- Utilize vector databases like Redis and NoSQL databases to handle large-scale datasets and outputs.
- Implement similarity search algorithms for efficient retrieval of information from generative AI outputs.
- Collaborate with domain experts to tailor generative AI solutions to specific business requirements.
- Conduct research and evaluation of advanced AI techniques like transfer learning and model compression.
- Establish evaluation metrics to assess the quality, coherence, and relevance of generative AI outputs.
- Ensure compliance with data privacy, security, and ethical considerations in AI applications.
- Leverage data engineering skills to curate, clean, and preprocess large-scale datasets.
What We're Looking For
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Minimum 1-3 years of experience in Data Science and Machine Learning.
- In-depth 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 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 skills to work with software engineering and operations teams for seamless integration and deployment.
- Excellent problem-solving 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.
- 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.
Nice to Have
- Apply trusted AI practices to ensure fairness, transparency, and accountability.
- 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.
- 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.
- Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring.
Technical Stack
- Languages & Frameworks: Python, R, TensorFlow, PyTorch, NLP frameworks (BERT, GPT, Transformer models)
- Cloud & Platforms: Azure, AWS, GCP, Azure Open AI GPT models, Hugging Face Transformers
- Data Stores: Redis, NoSQL databases
- DevOps & MLOps: Docker, Kubernetes, Git, Terraform, CloudFormation
EY is an equal opportunity employer.
