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5+ years of experience across a breadth of data science, AI and machine learning disciplines including, but not limited to: forecasting, natural language processing (topic modeling, semantic search, text classification), deep learning and GPU-based algorithms (CNN, LSTM), computer vision.
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FM Global is seeking a Machine Learning Operations Data Engineer II to join our AI/ML team to support Machine Learning Engineering, working very closely with Data Science, Data Engineering, Subject Matter Experts and Solution Architecture teams.
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Strong proficiency in programming (e.g., SQL, Python, R, MATLAB), database technologies (Oracle, mySQL, relational databases; graph databases are a plus), machine learning/deep learning (network architectures are a plus), dimensionality reduction techniques (e.g., PCA), and possible cheminformatics software suites.
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Expertise in data modeling, predictive and prescriptive analytics techniques, machine learning, and SQL query optimization; strong understanding of data governance, data quality, and data security principles.
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Degree must be in Network Engineering, Systems Engineering, Information Technology, Computer Science, Mathematics, Data Science, or related field (e.g., General Engineering, Computer Engineering, Electrical Engineering, Computer Science, Computer Forensics, Cyber Security, Software Engineering, Information Assurance, or Computer Security.
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Relevant experience must be in one or more of the following: computer or information systems design/development, programming, information/cyber/network security, vulnerability analysis, penetration testing, computer forensics, information assurance and/or systems engineering.
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Experience with Data Science, Machine Learning and Artificial Intelligence. Team Management Manage & Coordinate team of Data Steward, Business Intelligence, Data Engineering, Data Governance & Data Science.
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Implement and maintain machine learning solutions within Azure cloud environments, ensuring scalability, performance, and security. This role requires experience in Azure OpenAI, Large Language Models (LLMs), Python, and proficiency in developing applications using Streamlit, LangChain, Databricks, and Python frameworks such as Flask and FastAPI. The ideal candidate will be adept at building scalable machine learning models and deploying them to production environments and also being part of customer success teams.
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The Department of Homeland Security (DHS) is recruiting professionals to support a range of leadership roles in Data Science, including Data Science Manager, Data Engineer Team Lead, FISMA Support Metric Lead, Data Modeler, Data Security Officer and Operations Research Chief.
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As part of the Data Analytics team, the Lead Data Scientist will work closely with the Data Engineering team and business functions to solve real-world oil and gas midstream problems using machine learning, data science algorithms and artificial intelligence.
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You have passion and expertise in one or more of the following areas: risk analytics, data analytics, machine learning, SQL, Python, cloud security, network security, vulnerability management, data protection, threat intelligence & investigations, and identity & access management.
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4+ years of experience in machine learning, data science, or data analytics experience. Professional certifications (e.g., CISSP, GIAC, CISM, CCSP, CISA, AWS Security, AWS Advanced Networking Specialty, AWS Solutions Architect.
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Computer engineering, computer science, electrical engineering, electronic engineering, machine learning, photonics, radar, robotics. Computational Analytic modeling: experience engineering and tuning deep learning algorithms for data science.
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AI & Computational Sciences, Novartis Biomedical Research Leadership Role in Chemistry-based AI/Machine Learning. AICS is seeking a highly motivated and experienced leader in the field of Chemistry-based AI/Machine Learning to drive the frontier of drug discovery.
$212,000 - $318,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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The ML Research Scientist will also have a hands-on roll and is expected to customize and create various machine learning algorithms to operate over multi-domain data and optimizing the performance of those algorithms on the data.
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