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The Client Quantitative Analyst position is within the Client Protection organization supporting functions, including Fraud Prevention and Detection, Anti-Money Laundering (AML), Sanctions and Screening Compliance.
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5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
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Strong business and industry regulatory acumen complemented by claims adjusting knowledge, premium and medical billing familiarity, and industry best practices in risk management and fraud detection/prevention.
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Specific training on VISA Regulations and Regulations E is preferred 5 years’ experience with fraud lifecycle; prevention, detection, recovery in cards, including risk management, fraud prevention with hands-on fraud investigation, fraud/payment operations or management.
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LANGUAGE ABILITY : Able to read, analyze, interpret and advise regarding complex governmental regulations, legal opinions, claims laws and regulations, technical claims processes and procedures relating to fraud detection/prevention, and medical billing and reports.
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As our first Data Science hire focusing on Machine Learning at Circle, you’ll start by focusing on two critical problems: helping identify transactions and actors who might be acting illicitly and helping us better balance our reserves across a series of accounts to reduce systemic risk inside the company.
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While the focus of this job will be machine learning applications, there are times where we need to use data science to solve other problems and machine learning is not the only or optimal option.
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Working knowledge and/or hands on fraud detection experience with card products, card processors, card networks, and one or more fraud rule systems such as Defense Edge, FDWC, Falcon Expert, Tsys Card Guard, Tsys Determinator, Broadcom 3DS, Token Administration, Visa Risk Manager.
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Passion for Artificial Intelligence, Predictive Analytics, and Machine Learning technologies is a core requirement. Experience with AI, predictive analytics and the machine learning landscape is a huge plus.
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Machine Learning and Deep Learning: Good understanding of: ML algorithms like linear regression, logistic regression, etc., supervised, unsupervised, and reinforcement learning, AI Frameworks like TensorFlow, PyTorch, scikit-learn etc., Neural network, NLP, computer vision, and predictive analytics.
$163,300 - $244,900 a yearFull-timeExpandApply NowActive JobUpdated 21 days ago - UpvoteDownvoteShare Job
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As a Machine Learning Engineer at TRM Labs, you will collaborate with an experienced team of engineers, data scientists, and research scientists to build scalable systems to detect, prevent, and mitigate cryptocurrency fraud and financial crime.
$50,000 - $130,000 a yearInternExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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We’re looking for talented scientists capable of applying ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others.
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What you’ll bring to Circle: 5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
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You will be at the cutting edge of implementing State-of-the-Art (SOTA) Computer Vision (CV) and Vision Language Models (VLM) for conducting image retrieval, segmentation tasks, AI-assisted labeling, object detection, and visual question answering using geospatial datasets such as satellite and aerial imagery, full-motion video (FMV), ground photos, and OpenStreetMap.
$97,258 - $131,584 a yearFull-timeExpandApply NowActive JobUpdated 25 days ago - UpvoteDownvoteShare Job
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Champion the use of machine learning and advanced statistics and data science to optimize trade-off between fraud detection, customer impact and operational costs. Oversee the use of analytical fraud detection solutions as well as the implementation of fraud strategies, policy, and projects.
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machine predictive fraud detection jobs Company: Sysco
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