Python with Jonathan R.

Blue Cross Blue Shield

• Working with doctors to assess the effectiveness of interventions • Utilizing SQL, Python, and SAS to gather data on members • Running propensity score matching to perform observational studies pairing treated members to control members. • Producing visualizations and reports to present results to internal clients.

Reynolds Consumer Products

•Created daily HTML newsletter with an automated web scraping script in Python. •Created an automated Python script to download API data to be stored in a SQL server •Used regex to extract contact details and company names from raw text data.

Metis

Metis is a 12-week immersive, project-based bootcamp that trains Data Scientists to acquire, clean, store, query, and analyze data employing several tools such as Python, PostGreSQL, MongoDB, AWS, Docker, etc. Each project results in a presentation which includes data visualizations created through matplotlib, plotly, D3, etc. and can include demos of web apps created using Flask, HTML, CSS, and Javascript. Graduates of this program develop a broad range of skills applicable to working with, visualizing, and presenting data to all audiences while creating key insights and useful applications using machine learning. •Built machine learning models as backends to Flask apps. •Utilized Python to obtain, clean, and analyze data. •Stored large datasets in MongoDB and PostgreSQL databases. •Extracted data from open sources using web scraping.

Brightblue Consulting

•Calculating ROI utilising market mix modelling to evaluate marketing initiatives •Performing constructing and improving econometric models utilising R and Excel •Creating intuitive data visualisations to clearly communicate the results to all audiences •Translating complicated statistical analyses into clear, actionable insights

ReputationInc

• Providing a deeper insight into stakeholder relations to find best performing areas and areas of improvement. • Utilizing SPSS, Excel, and Tableau to produce analysis and easily comprehensible visual representations of data. • Managing online surveys to collect stakeholder data. • Regularly cleaning and refining data to obtain the maximum benefit from analysis.

World Food Programme

•Consulting with a team of MSc Development Management Candidates •Collecting macroeconomic data from Latin American countries •Utilizing STATA to analyze the relationship between violence and low development and Latin American migration.

Lake Forest College

London School of Economics

Native Proficiency

Native Proficiency