Data Scientist (Computer vision)

As a Data Scientist at our company, you will be responsible for leading end-to-end data science projects, collaborating with cross-functional teams to identify opportunities, and develop actionable insights. Your key responsibilities will include: - Designing and implementing state-of-the-art computer vision models for object detection, image classification, segmentation, and tracking. - Developing and optimizing deep learning models. - Preprocessing and managing large-scale image and video datasets for training and evaluation. - Designing and implementing advanced machine learning algorithms and statistical models to solve complex business problems. - Analyzing large-scale datasets, including structured and unstructured data, to extract meaningful patterns and insights. - Developing and deploying scalable data pipelines and automation workflows. - Conducting thorough exploratory data analysis and communicating findings through visualizations and presentations. - Staying current with the latest advancements in data science, machine learning, and AI technologies. Qualifications: - 3 to 6 years of experience in data science, machine learning, or a related field. - Proficiency in programming languages such as Python or R, and experience with data manipulation and analysis libraries. - Strong theoretical foundation in machine learning algorithms and statistical modeling techniques. - Experience working with big data technologies and cloud computing platforms. - Expertise in object detection, image classification, and segmentation techniques. - Experience with deep learning frameworks like TensorFlow, PyTorch, or Keras. - Solid understanding of machine learning fundamentals, CNN architectures, transfer learning, and model evaluation metrics. Preferred Qualifications: - Experience with real-time vision systems or edge deployment. - Knowledge of video analytics and temporal modeling. - Contributions to open-source computer vision projects or relevant research publications. - Experience with multi-modal learning. As a Data Scientist at our company, you will be responsible for leading end-to-end data science projects, collaborating with cross-functional teams to identify opportunities, and develop actionable insights. Your key responsibilities will include: - Designing and implementing state-of-the-art computer vision models for object detection, image classification, segmentation, and tracking. - Developing and optimizing deep learning models. - Preprocessing and managing large-scale image and video datasets for training and evaluation. - Designing and implementing advanced machine learning algorithms and statistical models to solve complex business problems. - Analyzing large-scale datasets, including structured and unstructured data, to extract meaningful patterns and insights. - Developing and deploying scalable data pipelines and automation workflows. - Conducting thorough exploratory data analysis and communicating findings through visualizations and presentations. - Staying current with the latest advancements in data science, machine learning, and AI technologies. Qualifications: - 3 to 6 years of experience in data science, machine learning, or a related field. - Proficiency in programming languages such as Python or R, and experience with data manipulation and analysis libraries. - Strong theoretical foundation in machine learning algorithms and statistical modeling techniques. - Experience working with big data technologies and cloud computing platforms. - Expertise in object detection, image classification, and segmentation techniques. - Experience with deep learning frameworks like TensorFlow, PyTorch, or Keras. - Solid understanding of machine learning fundamentals, CNN architectures, transfer learning, and model evaluation metrics. Preferred Qualifications: - Experience with real-time vision systems or edge deployment. - Knowledge of video analytics and temporal modeling. - Contributions to open-source computer vision projects or relevant research publications. - Experience with multi-modal learning.