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MS or PhD in Computer Science, Statistics, Applied Mathematics, Physics or other quantitative fields with focus on AI, Machine Learning, Mathematical Algorithms, Probability and Statistical Modeling.
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The College of Social Sciences, Mathematics, and Education offers rigorous, high-quality undergraduate curricula in Actuarial Science, Computer Science, Criminology and Criminal Justice, Data Science, Education, History, International Studies, Mathematics, Political Science, Psychology, and Applied Sociology.
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Masters or PhD in Computer Science, Statistics, Decision Sciences, Applied Mathematics, Economics or the equivalent combination of education, training, and work experience. Work with a variety of Data/ Data science platforms such as Snowflake, Databricks, MLflow, AWS Sagemaker, leveraging Python, Spark/Scala, SQL.
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Economics, Statistics, Applied Mathematics, Mathematics, Financial Mathematics, Data Processing/Analytics/Science. Displaying knowledge or familiarity with industry financial instrument pricing tools and data sources e.g. Bloomberg, Refinitiv etc.
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Minimum of a Master's degree in applied mathematics, statistics, informatics, or computer science and at least 3 years of experience or an equivalent combination of education and experience required demonstrating expert knowledge or database and statistical programming required.
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Relevant PhD degree required in computational biology, computational neuroscience, applied mathematics, computer science, or related discipline required, with a strong bioengineering and/or molecular biology focus.
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In addition, the College offers graduate programs leading to master's degrees in Accounting, Applied Mathematics, Business Administration, Contemporary Instructional Design, Computer Science, Creative Music Technology, Data Science, Educational Leadership, Nursing, Social Work, and Special Education, as well as a Doctor of Nursing Practice.
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Preferred: PhD in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Statistics, Computer Science, Computational Biology, or related field.
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Earned graduate degree (Ph. D. or M.Sc. + 2 years relevant industry experience) in a highly quantitative discipline (e.g., machine learning, statistics, computer science, applied mathematics, theoretical physics, physical chemistry, econometrics, bioinformatics.
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Required: Bachelor's degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Statistics, Computer Science, Computational Biology, or related field.
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Possessing experience with one or more of the following key programming and data analytics tools: Python, R, SAS; Handle, manipulate and analyse data and information responsibly. As an Associate in our Risk Analytics and Modeling team, you’ll have the opportunity to apply your quantitative, modeling and analytical skills in a real world environment to develop or validate statistical, financial engineering, and AI/machine learning models in the areas of credit risk, market risk, assets and liabilities management, fraud detection, anti money laundering and other functional modeling and analytics area.
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A PhD in Computer Science, Information Systems, Cyber Security, Data Science, Engineering, Physics, Statistics, Applied Mathematics, Operations Research, National Security, or Political Science/Public Policy coupled with experience in research, systems analysis/ engineering, or cyber policy analysis; OR.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Our Flagship Data Science team is seeking a Senior Staff Data Scientist to work alongside the newly formed Applied Science team focused on building inference, algorithms, and models to identify and quantify complex cause and effect in the ecosystem.
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An advanced degree (master’s or doctoral) in a quantitative field, including but not limited to Computational Biology, Computer Science, Data Science, Applied Mathematics/Statistics, all relevant engineering and science disciplines.
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