Data Analyst

Jed Pimentel

Analyst

***** ****** ****, *******, **, 92584 951-***-**** ***.*.********@*****.***

Summary

Process-oriented data analyst with growing experiences in finance, energy, business operations & management. Graduated at University of California, Riverside with a bachelor’s in Economics and continually evolving through data science in order to improve efficiency in analytics with developing tech and administration. Developing insights from data is my passion.

Technical Skills

●Python – NumPy, Pandas, Matplotlib, Seaborn, Folium, scikit-learn (Machine Learning)

●SQL (MySQL, SQL Server, PostgreSQL, IBM DB2 etc.)

●Tableau, Jupyter Notebook, SharePoint, Cloud databases

●Excel (VBA / Pivot) & Microsoft Office

●Data cleansing, Exploratory data analysis, Data visualization

Soft Skills

●Strong verbal and written communication

●Workflow & process documentation for reporting

●Adaptable learning drive in fast-paced environments

●Dynamics CRM experience

●Liaison between both technical and non-technical teams

●Accounting and finance workflow knowledge

Projects

IBM Data Science Professional Certificate Capstone Project (in progress / link)

●Developed a process using Python appropriate libraries & Foursquare API in which the end-users or stakeholders save time in regards to finding the best location to move or rent in through comparative analysis, visualization, and k-means clustering.

●Reported findings in Jupyter Notebook going through the step-by-step process to easily present the data science methodology to both technical-savvy as well as individuals who are business or executive focused.

911 Montgomery, PA Emergency Calls Brief Exploratory Data Analysis (link)

●I cleaned the data set by making it a little bit more readable using Python Pandas. I then briefly performed exploratory data analysis where I look at the call totals per different types and created visualizations on the matter. I then followed up by looking specifically at one neighborhood called Abington.

●One insight I learned is that weekends have lower frequency of emergency calls. From the Tableau visualization, it is also quickly learned that vehicle accidents are the most common reason for emergency calls in Abington.

Rate Analysis 2018

●Gathered structured and unstructured data from EnergyCAP database through EnergyCAP reporting tools and SQL. Used primarily Python Pandas (& some Excel) for data cleaning, cutting expected cleaning time down from two months to two days.

●Cross-referenced utility bills, vendor rate structure documents, and the previously cleaned data to compare and contrast rate structures in order to maximise County budget.

Professional Experience

Admin Services Analyst I (Temporary) Riverside County EDA Energy Aug 2018 - Jan 2019

●Gather and elicit business requirements by interviewing customers, stakeholders, reviewing existing business documentation, and documenting existing processes and systems.

●Initialized dashboard setup and queries on EnergyCAP database for quick reporting.

Admin Analytics intern Riverside County EDA May 2016 - Sep 2016

●Utilized Excel to create Pivot Tables for reports and provided technical feedback in regards to new systems testing in order to revise procedures and training guidelines.

Education

Bachelors, Economics 2015 University of California, Riverside

●Related coursework: Econometrics, Population & Development

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