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Felipe Gomez

Felipe Gomez

Data Engineer

University of California Berkeley, University of California San Diego | San Diego

Technologies

My Portfolio Highlights

My New Course

Machine Learning with Tree-Based Models in Python

My New Course

Introduction to Python

My New Workbook

Course Notes: Introduction to Deep Learning with Keras

My New Course

Machine Learning with Tree-Based Models in Python

Data-driven magician, making the impossible possible.

My Work

Take a look at my latest work.

course

Introduction to TensorFlow in Python

course

Machine Learning with Tree-Based Models in Python

DataLab

Course Notes: Advanced Deep Learning with Keras

DataLab

Course Notes: Machine Learning for Time Series Data in Python

DataLab

Intermediate SQL

DataLab

Course Notes: Introduction to Deep Learning with Keras

course

Introduction to TensorFlow in Python

My Certifications

These are the industry credentials that I’ve earned.

Other Certificates

General Atomics Aeronautical Systems Lean Green Belt Certification

University of Washington Business Intelligence and Database Development

Microsoft Microsoft Certified: AZ-900: Microsoft Azure Fundamentals

Microsoft Microsoft Certified: DP-900: Microsoft Azure Data Fundamentals

Microsoft Microsoft Certified: Pl-300: Microsoft Certified Power BI Data Analyst Associate

DataCamp Course Completion

Take a look at all the courses I’ve completed on DataCamp.

Courses

Introduction to Python
Introduction to SQL
Introduction to Power BI
Intermediate SQL

My Work Experience

Where I've interned and worked during my career.

Helix Electric | Aug 2023 - Present

Senior Data Engineer / Business Intelligence Engineer

N/A

General Atomics | Jan 2022 - Present

Senior Business Intelligence Engineer

▪ Successfully apply CARTs and Deep Learning machine learning models to reduce the number of operation failures, quality defects and manufacture latency ▪ Innovated strategic competitive bid and proposal estimate processes for contracts by applying Monte Carlo and Wright Crawford Learning Curves statistical analysis with Linear and XGBoost Regressor models ▪ Engineered a MRP Supply-Chain statistical analysis application to optimize production control and manage inventory levels by leveraging Azure Synapse, Databricks and Power BI ▪ Established KPIs and data visualizations for 30+ facilities to provide performance visibility by developing complex data models and data warehousing in Power BI, driving an overall 10% increase in efficiency YoY ▪ Spearheaded corporate data migration to Azure DataLake Storage, optimized data warehousing models and SQL queries, and enhanced ML models for scalability and efficiency, minimizing downtime and business interruption ▪ Consult Senior Directors and VP of Manufacturing in generating business intelligence strategies, enhancing strategic decision-making between cross-functional teams and ROI projects over $5M annually
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General Atomics | Oct 2017 - Jan 2022

Database Enginer

▪ Pioneered the MQ-9B Certification Database as the foundation for future UAV contracts by architecting and maintaining proprietary Access and DOORS Databases ▪ Engineered the automation of formal engineering reports, documentation and Power BI data visualizations by designing complex SQL queries, data models and Access/DOORS reports ▪ Enhanced existing MS SQL Server, Access and DOORS databases by applying standard database architecture best practices, removing business disruptions by maintaining robust and efficient databases ▪ Perform data engineer, data integration, data preprocess and standard ETL techniques using SQL and Visual Basic macros to ensure data validity and compliance to customer requirements

UCSD Data Science and Engineering Capstone | Jan 2021 - Jun 2021

Data Scientist

▪ Invented the Fire Potential Index (FPI) ML Model, adopted by SDG&E and UCSD research facilities, resulting in accurate models to assess fire risks across San Diego County and minimize high-risk seasonal fires ▪ Deployed KMeans++, PCA and NLP techniques with Random Forest and XGBoost Regressor models by training on weather satellite and geospatial data, attaining reliable and powerful predictive models ▪ Improved the model prediction accuracy over 25% by performing hyperparameter tuning and cross validation, achieving Mean Absolute Error reduction by 75%, from 1.6 to 0.4 Fire Potential Units ▪ Optimized model pipeline by using Synoptic Data REST API tools to upload over 10 million MesoWest Time Series records to AWS S3 Bucket, training models in AWS SageMaker and leveraging PySpark for big data processing

My Education

Take a look at my formal education

Masters in Data Science and EngineeringUniversity of California, San Diego | 2021
Bachelor's in MathematicsUniversity of California, Berkeley | 2017

About Me

Felipe Gomez

Current Senior Business Intelligence Engineer looking to step into the next role as a Data Scientist or AI/Machine Learning Scientist. I am very enthusiastic about working with data and discovering insight by working with data!

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