Data Scientist, Business Insights

MICHAEL G. MULLER

**.******@*******.***

917-***-****

*** **** ******, ***. **, Brooklyn NY 11220

PROFILE

Data Scientist, Adjunct Professor of Computer Science, a multi-faceted analyst, developer, and thought-partner. Able to effectively manage the data pipeline.

EDUCATION

CUNY School of Professional Studies, New York, New York M.S., summa cum laude, Data Science, January 2019

Awards: Dean’s List (2017-2019)

SUNY Stony Brook University, Stony Brook, New York B.A., Political Science, May 2014

EXPERIENCE

July 2018 -

April 2020

Context Travel, New York, New York

Data Scientist, Business Insights

Managed up and down within Business Insights to direct company with various insights, including visualizations, revenue models, and funnel metrics. Assessed, created, and validated predictive and statistical models including recommender systems and perishable inventory forecasting. Validated hypothesis with statistical analysis. Implemented machine learning via Python, pyTorch, Jupyter Notebooks, AWS, seaborn, R, SQL. ETL’d various sources into and maintained data warehouse. Worked to create new revenue streams and heighten company-wide growth. Brought in revenue via lead generation within first month as sole developer to webscrappers using Scrapy, Selenium, Javascript, and various APIs. Created and maintained a data- driven work culture via dashboarding and metric management with Periscope. June 2018 –

Present

CUNY LaGuardia Community College, Queen New York

Adjunct Professor of Computer Science

Instruct undergraduate students in online and in-person computer science courses, including C++ for Engineers, Advanced C++, Introduction to Python. Jan 2014 –

Dec 2016

Free-lance Python Developer, Self-Employed

Developed and maintained Amazon Echo skills (applications) and webscrappers. SKILLS AND TOOLS

• Python

• SQL (redshift,bigquery)

• Data Visualizations

• Tableau, Periscope

(Dashboarding)

• Microsoft Excel

• Cloud architecture (AWS)

• Natural Language Processing (NLP)

• Machine Learning (ML)

• Google analytics

• Bayesian Statistics

• R language

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