Senior Data Scientist at EY

Short Description:

We are hiring a Senior Data Scientist at EY GDS Consulting in Bengaluru. The role requires a minimum of 4 years of experience in Data Science and Machine Learning, with expertise in NLP, Generative AI, LLMs, MLOps, and AI solution Architecture. The candidate will play a key role in developing and implementing cutting-edge AI solutions, collaborating with stakeholders, and staying updated on the latest advancements in generative AI techniques. Strong proficiency in programming languages like Python, knowledge of cloud platforms, and experience in data engineering are essential. The position emphasizes collaboration, innovation, and adherence to trusted AI practices.

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Job Title: Senior Data Scientist - EY GDS Consulting

Location: Bengaluru (Remote options available nationwide)

Compensation: Competitive

Requisition ID: 1451058

About Us: At EY, we offer a unique opportunity for you to shape a career as distinctive as your individuality. With a global presence, supportive environment, inclusive culture, and cutting-edge technology, we empower you to evolve into the best version of yourself. We value your distinct voice and perspective, counting on you to contribute to EY's continuous improvement. Join us to craft an exceptional experience for yourself and contribute to building a better working world for all.

Role Overview: Senior Data Scientist

We are actively seeking a seasoned Senior Data Scientist with a minimum of 4 years of experience in Data Science and Machine Learning. The ideal candidate will have expertise in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will be instrumental in developing and implementing advanced AI solutions, utilizing your technical prowess. A deep understanding of AI technologies, coupled with experience in designing and implementing cutting-edge AI models and systems, is essential. Additionally, proficiency in data engineering, DevOps, and MLOps practices will be valuable in this role.

Responsibilities:

Technical Contributions:

• Contribute to designing and implementing state-of-the-art AI solutions.
• Assist in developing and implementing AI models and systems, focusing on Language Models (LLMs) and generative AI techniques.
• Collaborate with stakeholders to identify business opportunities and define AI project goals.
• Stay abreast of the latest developments in generative AI techniques, evaluating their potential applications in addressing enterprise challenges.
• Utilize generative AI techniques, such as LLMs, to devise innovative solutions for industry-specific use cases.
• Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to enhance generative AI capabilities.
• Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment.
• Utilize vector databases (e.g., Redis) and NoSQL databases for efficient handling of large-scale generative AI datasets and outputs.
• Implement similarity search algorithms for accurate retrieval of relevant information from generative AI outputs.
• Collaborate with domain experts, stakeholders, and clients to tailor generative AI solutions to specific business requirements.
• Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression.
• Establish evaluation metrics and methodologies 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 for curating, cleaning, and preprocessing large-scale datasets for generative AI applications.

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field (Ph.D. is a plus).
• Minimum 4 years of experience in Data Science and Machine Learning.
• In-depth knowledge of machine learning, deep learning, and generative AI techniques.
• Proficiency in 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 (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 for seamless integration and deployment of AI models.
• Excellent problem-solving and analytical skills, translating business requirements into technical solutions.
• Strong communication and interpersonal skills, collaborating 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 for 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 for building and managing 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.

EY is dedicated to building a better working world, creating long-term value for clients, people, and society while fostering trust in the capital markets. With diverse teams across 150+ countries, enabled by data and technology, EY provides assurance and assists clients in growing, transforming, and operating. Our multidisciplinary approach spans assurance, consulting, law, strategy, tax, and transactions, allowing us to address complex global challenges with innovative solutions.

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