Masters degree in Statistics, Business Analytics, Applied Math, Operations Research, Economics, or a related quantitative field and 4 years of industry data science experience e.g., Data Scientist, Applied Data Scientist, Business Analyst, or related position. Work experience may have been gained prior to earning Masters degree. Work experience should include 1 year of work experience as a technical lead and experience inbr predictive models e.g., generalized linear models, logistic regression, random forests, boosting models, causal inference experimentation and general statistical modeling, andbr hypothesis testing.br SQL skills e.g., Snowflake, Postgres and Redshift..br a statistical scripting language e.g., R or Python..br a data visualization tool e.g., Tableau, Power BI, etc..br This position is fully remote and may telecommute from any location in the U.S. Occasional travel to companys offices for work reasons may be needed.br br br The Beneficiary qualifies because Beneficiary earned a Master of Science degree in Business Analytics from the University of Illinois in 2019. The Beneficiary also earned the necessary 4 years of work experience because they worked at Dunnhumby as a Lead Applied Data Scientist from April 2013 to August 2018 65 months; and Mu Sigma Business Solutions as a Senior Business Analyst from September 2011 to March 2013 18 months, which is a related position; Amazon as a Data Scientist from January 2020 to September 2020 9 months; Data Scientist II from October 2020 to February 2022 16 months. While employed with the aforementioned employers, the Beneficiary also received the special skills and requirements, including predictive models e.g., generalized linear models, logistic regression, random forests, boosting models, causal inference experimentation and general statistical modeling, and hypothesis testing; SQL skills e.g., Snowflake, Postgres and Redshift.; and statistical scripting language e.g., R or Python. necessary for the proffered position.
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