Data Scientist

We are seeking an experienced Data Scientist specializing in Computer Vision to join our AI and Machine Learning team. The ideal candidate will have a strong background in deep learning, image processing, and model deployment, with a track record of delivering innovative computer vision solutions. You will work on a variety of projects involving object detection, image segmentation, fraud image detecion, and other vision based applications.

Responsibilities

AI models developments:

• Develop and implement state-of-the-art computer vision algorithms for object detection, classification, segmentation, and recognition.
• Research and experiment with deep learning architectures such as CNNs, RNNs, GANs, and transformers for image and video analysis.
• Preprocess and annotate image datasets to enhance model training.
• Optimize and fine-tune computer vision models for performance, accuracy, and efficiency.
• Deploy models to production environments and integrate them into scalable AI driven applications.
• Work with cross-functional teams, including software engineers and product managers, to align AI solutions with business objectives.
• Stay up to date with the latest research and advancements in the field of computer vision and deep learning.
• Document methodologies, findings, and model performance metrics for knowledge sharing and transparency.

Security, Compliance & Ethics:

• Implement security measures for all AI deployments to guard against unauthorized access, risks, potential breaches.
• Ensure AI models comply with ethics and compliance rules of the company

Collaboration:

• Work closely with other Business teams to align AI strategy with broader organizational goals.
• Mentor junior team members, providing guidance and training.

Qualifications

• Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

Preferred Experience:

• 2-5 years of experiences

Job-Specific Skills:

• 2+ years of hands-on experience in data science with a focus on computer vision.
• Proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Strong knowledge of image processing libraries like OpenCV and image annotation tools.
• Experience in training and deploying deep learning models in cloud environments (AWS, Azure, GCP).
• Familiarity with MLOps best practices for model lifecycle management and monitoring.
• Solid understanding of classical computer vision techniques and their applications.
• Ability to work with large-scale datasets and distributed computing frameworks.
• Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.
• Excellent communication skills and the ability to collaborate with multidisciplinary teams.