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You will apply classical ML algorithms and cutting-edge deep learning (DL) 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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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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Experience in statistical detection of potential healthcare fraud and abuse, using tools, such as predictive modeling, development of mathematical models, neural networks, healthcare data analytics, and data mining.
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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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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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The Opportunity As a Computer Scientist/Engineer on the Fraud Team, you will be at the forefront of developing and executing an innovative strategy utilizing Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Large Language Models (LLM), and Multi-Agent Systems to combat a variety of fraudulent activities.
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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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Assists with the implementation and administration of the programs for fraud prevention and detection, information security, physical security, business continuity planning, and vendor management.
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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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Identify and analyze new fraud detection features using SQL, Databricks, and Python. Engage in ML model building activities for fraud detection (approximately 20% of the role.
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Maintenance Technician - Plastic Injection MoldingPosition Overview: The Maintenance Technician is responsible for troubleshooting, repairing, and performing preventative and predictive maintenance tasks related to plastic injection molding machinery, mold set-up, and PLC programming.
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We need an experienced data engineer like you to help our clients find answers in their big data to impact important missions—from fraud detection to cancer research to national intelligence.
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Lead predictive maintenance efforts including vibration analysis, oil analysis, vessel thickness, code inspections, pressure relief device inspections, back-flow prevention inspections, ultrasonic leak detection, and infrared analysis.
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Develop and maintain machine learning models for tasks such as financial forecasting, fraud detection, anomaly detection, risk assessment, and investor sentiment analysis. Stay up-to-date on the latest advancements in AI and machine learning, identify potential applications for the finance function, and propose relevant pilot projects.
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Essential Functions Provides basic preventative and predictive maintenance and repair of material handling systems in mainly mechanical power transmission and will work to build stronger skills in electrical and PLC/controls and welding/fabrication.
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machine maintenance predictive fraud detection jobs Company: Pinnacle Financial Partners
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