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Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch.
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Proficiency in advanced analytics techniques such as data mining, predictive modeling, machine learning, and artificial intelligence. Strong knowledge of advanced statistical methods, predictive modeling, machine learning algorithms, and artificial intelligence.
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Minimum of 15 years of professional experience in advanced Data Science domains such as predictive modeling, Large Language Models, machine learning, text mining, geo-spatial modeling, time series forecasting, optimization.
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Strong technical and consultative experience managing ESI through the EDRM including staging, processing, culling, email threading, clustering, communication analysis, machine learning, predictive modeling, etc.
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This role demands a blend of expertise in data science and a deep understanding of the semiconductor industry, aiming to harness advanced data analytics, predictive modeling, and artificial intelligence to address complex business challenges.
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Manage matters within Cardinal Health's internally hosted E-Discovery platform including processing, data culling, email threading, predictive analytics and workflows, tagging layout design and implementation, custom field creation, batch creation, search creation, production sweeps and QC, and production creation and transfer all with an eye toward best practices.
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Social media analysis and predictive modeling. Molecular, cellular, ecosystems, marine science, and biology research. These teams develop biologically inspired, revolutionary technological innovations in systems and synthetic biology, materials science and engineering, biotechnology tools and cognitive neuroscience.
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8 years of eDiscovery Project Management/Consultant experience preferred. Conduct preservation, collections and processing using the following tools: EnCase, Cellebrite, Nuix, Heureka, Relativity One, M365 Compliance Center.
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Perform advanced statistical analyses, data mining, and predictive modeling to identify actionable insights and solutions. In this roles, you will be responsible for the end-to-end process of understanding data requirements, modeling, validation, and deployment.
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Nanofluidics and microfluidics. Systems and synthetic biology. Appointees to the Specialist series engage in specialized research, professional activity, and University and/or public service. The ICB is a uniquely interdisciplinary research alliance led by the University of California, Santa Barbara, in collaboration with the Massachusetts Institute of Technology, the California Institute of Technology and partners from the Army and industry.
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Chemistry and biochemistry. Psychological and brain sciences. Cellular structural materials. The Institute for Collaborative Biotechnologies (ICB) is an Army-sponsored University Affiliated Research Center (UARC.
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Execute complex spatial and 3D analysis using Esri and other geospatial software to aid in project scoping and predictive modeling. Cultural Resources Management GIS Specialist. Bachelors degree in archaeology, anthropology, GIS, Geography, or related field required.
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Leverage modern ML/NLP methodologies (e.g., deep learning), computing hardware (e.g., GPUs), cloud infrastructure (AWS/Azure), open-source modeling frameworks (e.g., TensorFlow, Keras, PyTorch, XGBoost.
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DBMI has research and/or service programs in the following areas: Clinical informatics, clinical research informatics, biomedical data modeling and ontologies, biomedical natural language processing and information retrieval, medical artificial intelligence, privacy technology, global health informatics, equity in informatics, and translational bioinformatics.
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Experience with data modeling, statistical analysis, and predictive modeling techniques. Strong proficiency in SQL, Excel, and data visualization tools (e.g., Tableau, Looker, PowerBI.
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