Senior Manager/Manager - Data Scientist

EYlinkedin.com

Oct 7, 2026, 10:05 PM2w ago

Full-timeColombo, Western ProvinceData scienceManager (8+ yrs)

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About the role

The Senior Manager/Manager - Data Scientist at EY GDS Data and Analytics is responsible for designing and implementing advanced AI solutions, with a focus on generative AI, NLP, LLMs, and MLOps. The role involves collaborating with stakeholders to identify business opportunities, developing and deploying AI models, integrating with APIs and libraries, and ensuring compliance with data privacy and ethical standards. Candidates should have a strong background in data science, machine learning, and AI solution architecture, as well as experience with cloud platforms and data engineering. EY offers a global, inclusive environment with opportunities for professional growth and innovation in AI.

Must have

Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus.
Minimum 8-11 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 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 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 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.

Nice to have

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.

Technologies

AWS
Azure
CI/CD
CloudFormation
Computer Vision
Data Engineering
Data Science
Deep Learning
DevOps
Docker
GCP
Generative AI
Git
Hugging Face
Infrastructure as Code
Kubernetes
LLM
Machine Learning
MLOps
Model Deployment
NLP
NoSQL
Python
PyTorch
Redis
TensorFlow
Terraform
Transformers
Vector Databases