Data Scientist with a focus on Computer Vision in Sigma Software

Step into the role of a Data Scientist at Sigma Software, with a focus on Computer Vision. In this dynamic position within our Data Competency Center, you will spearhead innovation, craft solution architectures, and participate in pre-sales activities, leveraging the forefront of Computer Vision technology.ProjectWe are a team of 160+ professionals. We are very different, but a few things make us a true team: a genuine passion for our work, friendliness, and inexhaustible optimism, no matter what. As a Middle Data Scientist joining BU003 Data Competency Center, you will play a pivotal role in shaping and driving its endeavors. Responsibilities:- Define and refine technical requirements for Computer Vision projects in close collaboration with clients and Team Leads.- Lead the creation and implementation of advanced Computer Vision models for object detection, image classification, and real-time video analysis.- Incorporate classical machine learning techniques, such as clustering, classification, and anomaly detection, into Computer Vision projects to enhance accuracy and efficiency.- Work with a variety of data sources to prepare and optimize data for Computer Vision applications, ensuring robust model training and performance.- Guide the integration of Computer Vision models into production systems, focusing on real-time performance and scalability.- Stay abreast of emerging trends and technologies in Computer Vision, experimenting with new tools and methods to push the boundaries of current models and solutions.- Communicate the value and impact of Computer Vision projects to stakeholders, effectively translating complex technical achievements into strategic business advantages.Requirements - Established expertise in Computer Vision, reinforced by a strong proficiency in Python and a deep understanding of essential frameworks such as OpenCV, TensorFlow, and PyTorch. - Comprehensive knowledge and hands-on experience with various neural network architectures, including Convolutional Neural Networks (CNNs), Fast R-CNN, VGG, ResNet, YOLO, and SSD, for tasks such as image classification, object detection, segmentation, and real-time video processing. Familiarity with implementing techniques like transfer learning, data augmentation, and fine-tuning to optimize model performance.- Solid background in classical machine learning techniques, with a proven ability to integrate these methods with advanced Computer Vision technologies effectively.- Demonstrated success in managing and analyzing diverse data sources, including structured, unstructured, and real-time data streams, to prepare and optimize data for Computer Vision models.- A commitment to ongoing professional development, with a focus on staying abreast of the latest advancements in Computer Vision methodologies, tools, and classical machine learning techniques.- At least an Upper-Intermediate level of English.Personal profile- Demonstrated problem-solving and analytical thinking skills, with a proven track record of applying these skills to real-world challenges to identify problems, gather relevant data, and develop creative solutions.- Continuous learning mindset, ensuring you stay up to date with the latest advancements in deep learning and adapt skills accordingly.- Actively participate in the evaluation of new tools for analytical data engineering or data science.