I'm Patrick Salsbury

and I like .

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Who am I?

My name is Patrick Salsbury and I am a Data Science Major at the University of California, San Diego after transferring from De Anza College where I obtained my Associates in Computer Science. As someone who has always loved mathematics and programming, developing an interest in Data Science and Data Engineering was a natural pathway for me. With rate that technology is evolving today, I think it is fascinating how businesses are discovering new ways to utilize big data and it excites me even more as I hope to dig deeper into the industry.

Education

University of California, San Diego

September 2021 - Present

B.S. - Data Science

Relevant Coursework:
Data Management, Machine Learning Foundations, Intro to Deep Learning, Applications of Data Science, Data Analysis & Inference, Business Analytics
Involvements:
- Delta Sigma Pi : President, Chancellor, Vice President of Scholarships & Awards
- Data Science Student Society : Member

De Anza College

September 2018 - June 2021

A.S. - Computer Science

Relevant Coursework:
Data Science Fundamentals, Data Structures & Algorithms, Object Oriented Analysis and Design
Involvements:
- Honor Society : Member
- Computer Repair Technician

Additional Education

IBM Data Engineering (Coursera)
Skills:
MySQL, PostgreSQL, IBM DB2, Apache Spark, Apache Airflow
Google Data Analytics (Coursera)
Skills:
Python, SQL, Excel, Tableau, R

Skills

Languages:
Python, SQL, Java, Html, CSS
Databases:
PostgreSQL, MySQL, IBM DB2, SQLite, MongoDB
Libraries:
Pandas, Sci-Kit Learn, Tensorflow, PySpark, SciPy, Plotly, Seaborn
Softwares:
AWS, Azure, Jira, Git Version Control, Databricks, Power BI, Tableau, Retool

Experience

Data Science Intern

Tesla - Palo Alto, CA
June 2024 - Present

Data Science & Engineering Intern

EverCharge - Palo Alto, CA
June 2023 - September 2023
  • Identified bugs, hardware issues, and installation problems that were previously unknown affecting 5-10% of all products by performing time series analysis, inferential analysis, and anomaly detection.
  • Engineered Retool dashboards to showcase data validation and integrity issues while optimizing PostgreSQL database queries.
  • Published 3 different data science reports that communicated answers to stakeholders’ questions and highlighted areas of concern.
  • Initiated a proof-of-concept project that involved training an ML anomaly detection model to identify abnormal device behavior.

Computer Science Coach

TheCoderSchool - Encinitas, CA
February 2023 - March 2023
  • Coached students of levels ranging from Elementary to Highschool within the topics of computer science and software engineering
  • Designed personalized curriculum including projects and learning paths to support individuals from different backgrounds and experience
  • Supported the development of apps in Python and Scratch over 4-6 week time while simultaneously teaching the fundamentals of coding

Data Science Intern

HM Electronics - Carlsbad, CA
June 2022 - September 2022
  • Analyzed customers device data improving the quality of production and customer relationships by showcasing areas of concern.
  • Led sprint presentations to showcase findings using Python, SQL, and Power BI to influence the decision-making of the product managers and software engineers.
  • Collected semi-structured console log data from 100+ customer devices to ingest into a Azure Blob Data Lake.
  • Automated the ETL process on 30+ million raw records of data at once using Apache Spark on Databricks(Microsoft Azure).
  • Predicted customer device failure using Classification and Clustering ML models to isolate variable indicators for tech support.

Mathematics Tutor

De Anza College - Cupertino, CA
August 2019 - April 2021
  • Instructed mathematical subjects such as Precalculus, Calculus, Differential Equations, and Linear Algebra to college students
  • Administered individual study sessions and group workshops ranging anywhere from 5-10 people at once
  • Maximized individual tutee’s test results up to the 90%+ range and increased rates of passing by more than 50%.

Projects

E-commerce Recommender System

December 2023
  • Developed a machine learning model catered for an e-commerce recommender system using Sci-kit Learn, H2o AutoML, and tensorflow
  • Performed exploratory data analysis, feature engineering, model training and validating, and hyperparameter tuning in order to obtain a model with an accuracy, F1-score, and ROC-AUC of 0.71, 0.72, 0.79 respectively.
  • Deployed the finalized Collaborative Filtering Tensorflow model using Flask and HTML to emulate a real-world recommender system.
Github🡵

Real-Time Weather Data Dashboard

April 2023
  • Constructed dynamic dashboards visualizing real-time weather updates using Tableau, MongoDB, and weather APIs.
  • Highlighted temperature, humidity, and other attributes using Apache Airflow to build an ETL batch processing pipeline that ingested, transformed, and loaded the data while performing various quality checks.
Github🡵

Popular Youtube Videos Title Generator

March 2023
  • Utilized Youtube APIs to analyze recent top 50 trending videos and predict a new possible trending video title.
  • Established an ETL pipeline to populate an SQLite database after processing words using Pandas and NLTK.
  • Generated possible trending video titles using sentence linguistics, unigram NLP models, and N-gram NLP models.
Github🡵

Recipe Ratings Analysis and Predictor

February 2023
  • Analyzed 234,429 different recipe reviews given on Food.com to discover underlying associations and trends regarding rating.
  • Concluded statistically significant results using hypothesis testing and after performing exploratory data analysis.
  • Developed a Decision Tree model using CV grid search after testing models using SKLearn pipelines.
Github🡵

Best Companies to Work For

July 2021
  • Showcased the top 500 best companies to work for in 2021 according to Forbes.com using Python and SQL.
  • Extracted and transformed data using web-scraping and data processing to store into an SQLite3 database.
  • Showcased the top 500 best companies to work for by utilizing embedded-SQL queries and Matplotlib.
Github🡵

A Programmer's Pay Analysis

June 2021
  • Performed EDA using Python to investigate a programmer’s salary and contributing factors
  • Assembled Pandas, NumPy, and Matplotlib to clean, query, and visualize over 64461 data entries.
  • Concluded positive associations between pay and hobbyist coding, language, education level, and experience.
Github🡵

Reaching out

Whether you are looking to fill a position for a role you think I would be a great fit for or whether you simply just want to chat, feel free to reach out! I always love to meet new people and learn new things so please connect with me on LinkedIn or contact me through email. Thanks!

Location
San Diego, California / San Jose, California
Email
p.r.salsbury@gmail.com
LinkedIn
Link
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