We are looking for a Chief Data Scientist to join our organization.

In this role, you will lead the delivery of a next-generation warehouse safety platform powered by advanced computer vision. The initiative focuses on elevating safety protocols in Amazon warehouses by leveraging video analytics to identify risks and unusual activities.

 

Responsibilities

• Direct the creation and rollout of computer vision solutions for detecting objects and anomalies, utilizing tools such as YOLO and Amazon SageMaker Ground Truth
• Enhance the effectiveness, scalability, and precision of models through techniques like hyperparameter tuning and data augmentation
• Evaluate and integrate large language models to support tasks like data annotation and extracting actionable insights
• Oversee the complete process of AI and machine learning model development, from data labeling to production deployment of inference pipelines
• Partner with ML Ops specialists to embed models into seamless pipelines that align with AWS best practices
• Guarantee the provision of high-quality labeled datasets using Amazon SageMaker Ground Truth for robust model training
• Review and improve the reliability of datasets and the performance of models to ensure accuracy in practical computer vision scenarios

 

Requirements

• Bachelor’s or Master’s degree in mathematics, statistics, computer science, data science, or a closely related area
• More than 7 years of experience in data science or a comparable field
• At least 2 years of experience leading and managing technical teams
• Participation in at least two end-to-end project cycles or involvement in multiple projects spanning various development stages
• In-depth expertise in computer vision algorithms and frameworks, with a focus on YOLO and contemporary object detection technologies
• Significant hands-on experience with Amazon SageMaker, including Ground Truth for data labeling and constructing scalable ML pipelines
• Advanced proficiency in Python, especially for data science, AI, and machine learning applications
• Strong command of AWS cloud-native services, including Lambda, DynamoDB, Aurora, S3, and SNS/SQS
• Proven ability to build and launch AI and machine learning solutions in production settings
• Knowledge of evaluation metrics such as precision, recall, and F1 score, and their application in refining models
• Excellent English communication skills, both verbal and written, at B2+ level or above

 

Nice to have

• Familiarity with AWS edge technologies like AWS Panorama for running computer vision workloads on IoT devices

 

We offer

• International projects with top brands
• Work with global teams of highly skilled, diverse peers
• Healthcare benefits
• Employee financial programs
• Paid time off and sick leave
• Upskilling, reskilling and certification courses
• Unlimited access to the LinkedIn Learning library and 22,000+ courses
• Global career opportunities
• Volunteer and community involvement opportunities
• EPAM Employee Groups
• Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn