Raul Torres

Sales & Business Development Manager • Customer Success Manager • San Antonio, TX, US

Data Analysis

Python

Data Science

MySQL

Natural Language Processing

Data Cleaning

Available for hire fromNegotiable

A data analyst with over two years of combined experience in sales, marketing, and analytics, as well as a degree in Biology.

A data analyst with over two years of combined experience in sales, marketing, and analytics, as well as a degree in Biology. Skilled at using Machine learning techniques, Python, SQL, and Natural Language Processing to help companies analyze customer data to determine the target market and increase revenue. Passionate about working with clients to identify marketing and sales opportunities based on company data. TECHNICAL SKILLS Microsoft Suite (Excel), Power BI, Python, Pandas, SQL, data cleaning and pre-processing including data mining, manipulation, visualization, and analysis. Machine learning algorithms, tools, and libraries with high business acumen and domain experience from various industries.

Projects

Twitter NLP Analysis

In this Twitter sentiment analysis project, we analyzed over 9,000 data points from Apple and Google, with positive, negative, and neutral responses. This was a supervised machine learning algorithm, where the training data was labeled with the correct sentiment (positive, negative, or neutral) for each tweet. The algorithm then learned from this training data to make predictions on the sentiment of new, unseen tweets. The results of the analysis showed that the majority of tweets about both Apple and Google were positive in sentiment, with a smaller percentage of negative and neutral tweets. This analysis provided valuable insights into public opinion about these two tech companies.See More

Telecommunication Churn Analysis

As a churn project focused on AT&T customers, my primary objective is to predict which individuals are likely to cancel their use of the company's products or services in the future. To do this, I have been provided with a dataset containing over 7,000 data points related to AT&T customers, including both binary and numerical features. Some examples of binary features include gender, internet service, and partnership status, while numerical features include monthly spending and tenure with the company. The target column in this dataset is labeled "churn," indicating whether or not a customer has cancelled their service. In order to effectively analyze and make predictions using this data, I have performed a number of preprocessing steps, including cleaning and scaling the data and encoding any categorical variables. I have then utilized a range of machine learning models to generate predictions, ultimately selecting the model that performs best through a process of grid search. By successfully identifying potential churners, I am working to help AT&T reduce customer churn and improve its bottom line.See More

Tanzania Water Wells Analysis

Tanzania is one of many countries facing water shortages in the face of climate change. In our dataset, provided by Taarifa and the Tanzanian Ministry of Water via DrivenData's competition "Pump it Up: Data Mining the Water Table," nearly half of the wells we studied are non-functional or in need of repair, which leaves countless people and families without reliable water access. We achieved an 85% accurate model which predicts which wells are functional, non-functional, and in need of repair. The most important features included Water Quantity, Extraction Type, and Payment Type: by accessing waterpoints with ample available water, well-documented and established extraction types, and requiring payment from users, we believe the Tanzania Water Fund can construct new wells with the best chance of lasting success. See More

Microsoft Movie Studio

Microsoft is a well-established technology corporation most known for creating computers and software. Unlike their competitors in the technology industry (Apple, Amazon, etc.), Microsoft does not currently produce original video content. If they were to compete in this medium, what factors would best contribute to their success? We sought out answers using database files from Box Office Mojo, IMDB, TheMovieDB, and The Numbers, which pointed toward certain times of the year, genres, and persons associated with reliable financial success. See More

Work History

Business Direct Representative & Closer

Smart Power SolarApr 2021 - Aug 2022 • 1 yr 5 mos● Generated over $1.3MM in sales by using direct marketing techniques like referral system, social media, and events to inform customers about the benefits of the product. ● Collaborated with management to train new sales associates, and create a strong company culture that resulted in higher retention and productivity. ● Used CRM tools like NetSuite to analyze business data in order to identify potential opportunities for growth and track current accounts in the pipeline.

Corp Member

City YearAug 2020 - Apr 2021 • 9 mos● Formed meaningful relationships and increased engagement through a program I developed to reward students at the end of the year. This increased engagement, performance, and promoted competition in a positive way. ● Assisted students with their classwork and served as a point person for any academic or socio-emotional needs. ● Gathered, cleaned, and analyzed student data to create data visualizations in order to report insights to stakeholders.

Education

University of Florida

Bachelor's Degree, BiologyAug 2017 - May 2020

Flatiron School

Bootcamp, Data ScienceSep 2022 - Jan 2023

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