Data scientist (Image Scientist)

As an Image Scientist at Adani, you will be responsible for:

• Developing and implementing advanced algorithms and models for image recognition, segmentation, and feature extraction.
• Collaborating with cross-functional teams to design and optimize image processing pipelines and workflows.
• Contributing to the development and enhancement of AI-based systems for image interpretation and understanding.
• Utilizing machine learning and deep learning techniques to extract meaningful insights from image data.
• Evaluating and validating the performance of image processing algorithms through rigorous testing and analysis.
• Communicating complex technical concepts and findings to non-technical stakeholders in a clear and concise manner.
• Participating in the creation and maintenance of high-quality documentation and technical reports related to image science projects.
• Continuously exploring new methodologies and technologies to improve the efficiency and accuracy of image analysis processes.
• Adhering to industry best practices and standards while ensuring compliance with data privacy and security regulations.

Experience

• 2-3 years of experience in the Data Science and AI industry with a focus on image processing and analysis.

Education Qualification

• Bachelor’ or master’s degree or Ph.D  in Computer Science, Data Science, Artificial Intelligence, or a related field.

Certification required

• Certifications in machine learning, computer vision, or image processing would be an advantage.

Behavioural Skills

• Strong analytical and critical thinking skills.
• Excellent problem-solving abilities and attention to detail.
• Effective communication and collaboration skills.
• Adaptability and willingness to learn and explore new technologies.

Technical Skills

• Proficiency in programming languages such as Python, R, or Java.
• Experience with machine learning frameworks and libraries, such as TensorFlow, Keras, or PyTorch.
• Working knowledge of image processing tools and libraries, such as OpenCV, scikit-image, or PIL.
• Familiarity with deep learning architectures and techniques for image analysis.
• Experience with cloud platforms and services for data storage and processing, such as AWS, Azure, or GCP.