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Demonstrable expertise in an area of data science or analytics (e.g. machine learning, deep learning, NLP, computer vision, predictive modeling and forecasting, statistics) Significant coursework or professional experience in machine learning, deep learning, NLP, computer vision, predictive modeling and forecasting, statistics, or similar analytic domain.
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Role entails: actuarial pricing, rating, reserving, capital modeling, catastrophe modeling, data science, predictive modeling and machine learning and reinsurance. Role entails: actuarial pricing, rating, reserving, capital modeling, catastrophe modeling, data science, predictive modeling and machine learning and reinsurance.
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Experience with Root Cause Analysis, Six Sigma, Continuous Process Improvement, Lean Manufacturing, 6S, Process Optimization, Predictive modeling, Process Capability, PFMEA, Product Development, and Metrology Applications.
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Apply machine learning, econometrics/statistics, predictive modeling, return-on-investment analysis, simulation, and data visualization methods to support the development of health policy.
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Experience in Data Science, Data Mining, Machine Learning, Predictive Modeling best practices. Experience in Data Science, Data Mining, Machine Learning, Predictive Modeling best practices.
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Over 8 years of experience in machine learning, predictive modeling, statistics, computer science, bioinformatics, or computational biology, specializing in neuropsychiatric disorders. Lead projects in computational and predictive modeling using machine learning, generative AI, causal modeling, and other relevant techniques.
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Leadership of predictive modeling tools such as 3D rapid prototyping, AutoCAD Inventor or Solidworks, primary/secondary/tertiary/pallet/truck loading (i.e., TOPS), Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA) and/or others are a plus.
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Computational social science (including agent-based modeling and simulation, social media analysis, behavioral economics, game theory, predictive modeling) Social influence and disinformation, detection and mitigation of insider threat, industrial/organizational psychology, and teamwork and group dynamics.
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Deep expertise in data mining, statistical analysis, machine learning, and predictive modeling. Leverage predictive modeling and machine learning to forecast trends and customer behavior.
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The successful candidate will be responsible for overseeing the development and implementation of advanced analytics, data mining, and statistical modeling techniques to solve complex marketing and GTM challenges and drive business growth.
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This role focuses on enhancing our systems modeling capabilities, integrating multi-omics, neuroimaging, and clinical data specifically for biomarker and drug target discovery in these disorders.
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Master’s degree (or its equivalent) in statistics, mathematics, economics, computer science, data sciences, predictive modeling, or other quantitative disciplines and at least 6 years of relevant experience, preferred in AML/BSA, OFAC, or fraud modeling/analytics.
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As a data scientist on our team, you will employ predictive modeling, statistical analysis, and advanced analytics techniques to support solutions for talent management, employee surveys, compensation, and recruiting.
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This work will be performed in close collaboration with pediatric neurologist and epileptologist clinician researchers and faculty at NCH.The candidate should be able to leverage both structured and unstructured data sets to create analytical solutions using tools and/or methods in at least one of the following areas: statistical and predictive modeling, machine learning, natural language processing, and geospatial analysis.
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We leverage the predictive capability of our high-fidelity computational physics solvers, indigenous massively parallel supercomputer system, prototyping plant, and ballistics and mechanics lab to investigate a variety of high-rate physics phenomena.
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