Hire Freelance Anomaly Detection Specialists
Matej Kloska
Matej has more than 10 years of back-end applications development experience. He received his PhD in the field of informatics with a focus on time series and anomaly detection. He is passionate about reusable, testable, clean code and has experience in microservice-oriented clean architecture and container-oriented infrastructure with a focus on Kubernetes. He has wide hands-on experience as a developer, data engineer, and later as CTO. Matej loves back-end and machine-learning challenges.
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Mohamed A. Abdelhady
An adept machine learning engineer, Mohamed excels in creating ML-powered products across varied domains. His expertise spans computer vision for KYC, graphs in fraud detection, and anomaly detection for AML. Leading data teams, he ensures robust risk coverage. Mohamed's proficiency extends to developing ML solutions for fintech fraud detection, autonomous robots, and precision machinery. He oversees complete ML lifecycles, excelling in requirements gathering, model training, and deployment.
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Akram Zaytar
Akram is a machine learning engineer specializing in structured and Computer Vision data analysis. After finishing his Ph.D. in applied deep learning, he worked on prototyping and deploying anomaly detection systems. At IBM Research, he guided its intelligence services' climate modeling and ML tooling. Akram excels with end-to-end data-driven intelligence, business requirements analysis, data assembly, and the prototyping, onboarding, and monitoring of AI models.
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Manpreet Singh Minhas
Manpreet is a computer vision and deep learning engineer and developer who has taken many AI-based ideas from the research stage to production. He regularly shares his industry and research expertise in deep learning and computer vision by authoring technical articles on Medium's Towards Data Science. Manpreet's industry experience is backed by a master's degree in computer vision and deep learning, he is passionate about technology, and he loves to build cool stuff.
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Kshitij Kant
Kshitij is a data science professional with experience in behavior modeling, anomaly detection, and natural language processing. He has worked with datasets of varying sizes (KBs to scores of GBs) and his tools of choice are Python and Spark. Kshitij also has a background in web development using Node.js, React-Native, Docker, and CouchDB.
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Dávid Natingga, Ph.D.
Dávid helps his clients solve the most complex analytical problems using mathematics, data science, and technology. He has aided numerous clients, including big names like Infosys, Palantir, Suez, and TomTom. Dávid's top niche is high-frequency time series analysis. He makes the impossible possible. His inventions encompass robust Fourier transform, robust anomaly detection, and overcoming the curse of higher dimensionality. Dávid's strengths include curiosity, creativity, and persistence.
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Xavier Coubez
Xavier holds a PhD in particle physics and participates in one of the two main CERN collaboration projects. For five years now, he has been working as a postdoctoral researcher at Brown University (USA) and RWTH Aachen University (Germany), developing in-depth knowledge about deep learning. Xavier studied the performance of several generations of algorithms for 3D object identification and worked on medical imaging and genomics projects, eager to apply data analysis to medicine.
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Wesley Welch
After falling in love with statistics in college, Wesley learned Python as a means to facilitate his yearning to use data to answer questions. This has snowballed into his role as a data analyst for an insurance company and a software engineer specializing in machine learning for a risk-management startup. In both roles, he was given a blank slate to create novel solutions to myriad problems, and he sincerely enjoyed it. Wesley thrives in an environment where no two days are exactly the same.
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Artem Ryzhikov
Artem holds a PhD in machine learning (ML) and has seven years of experience in data structures as well as six years of ML research, two years of working at tech startups, and four years of team management. As a senior ML engineer, he has built a CV algorithm for a mobile app that reached second place in the App Store in a week with 1.5 million downloads. Artem has also worked on various other projects, including recommendation and search systems, text processing, and conventional data science.
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Denis Volk
Denis is a senior full-stack AI engineer and data scientist, highly skilled in modern generative tech (GPT-4, Midjourney, and more), machine learning, ETL pipelines, data analysis, mathematical modeling, big data, and MLOps. He has a PhD in mathematics, and his data science expertise includes probabilistic risk modeling, revenue forecasting, geospatial data analysis, handwriting recognition, anomaly detection in time series, data engineering, and team leading.
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Hiro Shioi
Hiro is a customer-facing data scientist. He excels at very high-level data science problems (ideation, road mapping, ROI estimation, solution and data architecting) to hands-on execution (data cleansing, feature engineering, modeling, operationalization). At General Electric, Hiro led a million-dollar digital transformation advisory project and developed 15 data science products across the healthcare, mining, telecommunications, manufacturing, transportation, power, and financial industries.
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