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Degree in a technical or quantitative discipline, like statistics, mathematics, physics, electrical engineering, computer science, or applied economics or finance (all levels welcome, from bachelor's to doctorate.
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Bachelor's degree in a STEM major or with STEM coursework learned in associated majors (Actuarial Science, Computer Science, Data Engineering, Data Science, Mathematics, Applied Mathematics, Statistics, Finance, Economics.
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PhD in Statistics, Computer Science, Mathematics, Economics or directly related fields is a plus. This presents an opportunity to create tremendous business value as we assemble a world-class applied machine learning team.
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Masters degree in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics or equivalent experience. PhD degree in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.
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Bachelor’s degree or higher in quantitative finance, economics, statistics, applied mathematics, engineering or comparable area. Bachelor’s degree or higher in quantitative finance, economics, statistics, applied mathematics, engineering or comparable area.
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MA/MS preferred in Public Policy, Economics, International Relations, Quantitative Social Science, Statistics, Applied Mathematics, Operations Research, or related fields. MA/MS preferred in Public Policy, Economics, International Relations, Quantitative Social Science, Statistics, Applied Mathematics, Operations Research, or related fields.
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We are currently seeking motivated and innovative individuals to join our applied machine learning team. Master’s degree in Statistics, Computer Science, Economics or directly related field.
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STEM (Science, Technology, Engineering, Mathematics) majors with quantitative emphasis – Statistics, Computer Science, Operations Research, Economics, Engineering etc. Applied knowledge of statistical analysis, experience with R, Python, Excel, etc.
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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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A degree, preferably in Economics, Econometrics, Engineering, Physics, (Applied) Mathematics, Accounting, Information Systems. A degree, preferably in Economics, Econometrics, Engineering, Physics, (Applied) Mathematics, Accounting, Information Systems.
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A Master's degree or higher in Business, Cost Estimating, Data Science, Economics, Engineering, Management Science, Mathematics, or Operations Research. A Bachelor's degree or equivalent in Business, Data Science, Economics, Engineering, Management Science, Mathematics, Operations Research or another related field.
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The position requires a deep understanding of computational linguistics, image processing, and Python programming. The Principal Data Scientist is a highly motivated and experienced individual proficient in advanced machine learning models, particularly language models, document understanding and analysis, and code generation.
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A Baccalaureate Degree from an accredited college or university with a major in Computer Science, Systems Engineering, applied Mathematics, Business Administration, Economics/Statistics, Telecommunications, Data Communications, or a related field of study; and2.
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Undergraduate degree in Actuarial Science, Applied Mathematics, Statistics, Economics, Computer Science, Data Science or Data Analytics or other quantitative major. Experience with: Modern Data & Analytics Technology such as Dataiku, Tableau, AWS, Spark Coding with SQL, Hive, Python/R, SAS, VBA, etc.
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Cluster-Bachelors Degree in Econometrics, Economics, Engineering, Mathematics, Applied Sciences, Statistics or job-related discipline or equivalent experience. We are looking for a full-time front end developer to develop and maintain front-end client applications that interactively display rich meteorological and fire datasets.
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