Data Scientist with a focus on Computer Vision (Data Competency Center) at Sigma Software
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Job Descrption
Company Description
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.
PROJECT
We 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 be pivotal in shaping and driving its endeavors.
Job Description
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
Actively participate in the evaluation of new tools for analytical data engineering or data science
Qualifications
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
English proficiency: Confident Intermediate level or higher (both written and spoken)
Additional Information
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 updated with the latest advancements in deep learning and adapt skills accordingly
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