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Bachelor’s degree in Analytics, Engineering, Statistics, Industrial/Organizational Psychology or related field. Master’s degree in industrial/organizational psychology, Data Analytics, or Statistics preferred.
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Have a robust statistics and data science background, in particular, deep understanding of the theory and principle of classic statistics, sampling surveys, experimental design, geostatistics, and other data modeling and analysis methods, including machine learning and artificial intelligence.
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The Statistics and Data Science department conducts a wide range of statistical and data science projects, engaging in statistical analysis, modeling, data linkage, statistical matching, disclosure control, small area estimation, and Bayesian analysis, to support all aspects of social science research.
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Master's degree in a quantitative field (Mathematical Finance, Computational Finance, Computer Science, Finance, Statistics, and Mathematics). 1+ years of experience in risk management, risk modeling or fixed income capital markets.
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Our areas of expertise include remote sensing, geospatial analysis, GIS, soil science, water quality and demand evaluation, agricultural systems, salinity and nutrient management, ecosystem restoration, statistics, and regulatory policy.
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As a Quantitative Research Intern, you’ll spend the summer learning trading fundamentals and completing real projects in financial modeling, data science and statistics. Who you are: Currently enrolled in a PhD program in mathematics, computer science, statistics, physics or a related field with a winter 2024 or spring 2025 anticipated graduation dateExperience using Matlab, R, Python or other analytical tools for quantitative researchExperience analyzing large data sets is not required, but preferred.
InternExpandApply NowActive JobUpdated 2 months ago - UpvoteDownvoteShare Job
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You will perform income at risk modeling and analysis, limits monitoring and reporting. Role: Risk Analyst, Income Risk Modeling. Perform analysis to identify issues and support changing scenario analysis or modeling requirements from market update, regulatory change or management strategic needs.
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The University of Chicago's Annual Security & Fire Safety Report (Report) provides information about University offices and programs that provide safety support, crime and fire statistics, emergency response and communications plans, and other policies and information.
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Bachelors and/or Masters degree in Actuarial Science, Mathematics, Statistics, Finance or a related field. Focus on loss reserving projects with additional engagements in pricing/ratemaking, predictive modeling, economic capital modeling, and loyalty rewards programs.
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Actuarial Science, Statistics, Mathematical Statistics, Applied Mathematics, Mathematics, Economics. A career in our Risk Modeling Services practice will provide you with the opportunity to contribute general insurance advice and consulting services to clients such as insurers, banks, regulators, and third party administrators.
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Creative data-driven solutions by employing data science techniques such as operations research, advanced statistics, feature engineering, machine learning/AI, predictive analytics, mathematical modeling, linear and non-linear regression, stochastic modeling, and mathematical optimization.
Full-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Successful applicants for this position will be working closely with traders, quants and other software engineers to implement and extend the different parts of our trading infrastructure including lowlatency trade execution services, tick data infrastructure, database service layers, exchange connections, back testing systems, GUIs, risk management systems, calculation and modeling engines and compliance monitoring tools.
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Primary focus on loss reserving but additional projects include pricing/ratemaking, predictive modeling, economic capital modeling, and warranty and loyalty rewards programs. BA/BS degree in Actuarial Science, Mathematics, Statistics, Economics, Finance, or related field.
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The successful candidate will have experience with data management, econometrics, and statistical modeling. Extensive background in applied statistics and econometrics. The EE Lab applies rigorous evaluation and modeling methods, including natural and field experiments, randomized controlled trials, behavioral economics, and machine learning, to help policymakers identify and generate evidence on innovative approaches and policy solutions to their most pressing environmental and energy challenges.
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Bachelor's or Master's Degree in Applied Mathematics, Statistics, Actuarial Science, Econometrics or other quantitative discipline. Experience in database maintenance, schema design and relational modeling and data technologies like R, Python, Spark, etc.
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modeling statistics jobs in Chicago, IL
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