榛内推 | Niche今日职位更新：亚马逊Data Scientist实习

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Amazon - Data Scientist Intern

【Niche榛内推】Amazon - Data Scientist Intern

【工作地点】Seattle, WA

【工作时间】10 weeks

【职位描述】

• Build statistical, predictive and machine learning models to drive sourcing accuracy.

• Promote data-driven decision making across the team, using tools such as Tableau, SQL, and Excel.

• Influence leaders to make thoughtful data decisions to provide the most consistent and usable data for all teams across the company.

• Combine expert knowledge of statistical methodology and analysis with advanced programming skills to support complex analyzes.

【职位要求】

• In process of receiving a graduate degree in an analytical area such as Machine learning, Computer Science, Physics, Mathematics, Statistics, Engineering or similar.

• Experience with modeling and analysis including machine learning, statistical analysis, operations research and management science and data mining.

• Experience with SQL (any variations thereof), Python/PySpark and/or Scala preferred; though experience with other analytics software (SAS, STATA, MATLAB

• Familiarity with AWS solutions such as Glue, S3, and Redshift., Mathematica, R/SparklyR) is acceptable.

Investment Reseach Company

Quantitative Analyst Intern

【Niche榛直推】Investment Research Company - Quantitative Analyst Intern

【实习地点】New York, NY

【实习时间】12 weeks

【职位描述】

• Compile and develop customer electric load data and sample statistics into meaningful reports for various internal and external clients.

• Ensure that standard statistical reports are complete each month for all assigned electric load samples.

• Assist Quantitative Analysts and Senior Analysts by designing spreadsheets, databases, procuring customer data, and producing necessary analytical reports.

【职位要求】

• Knowledge in Machine Learning and Data Science, including random forests, non-linear optimization, clustering and classification models, neural networks and deep learning.

• Macroeconomic Theory, DSGE, Econometrics and Time series modeling

• Central Bank Financial Stability, Systemic Risk and Contagion Models

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