Founder, CEO, Chief Data Scientist, and Lead Consultant

Founder, CEO, Chief Data Scientist, and Lead Consultant for Premier Analytics Consulting, LLC. Manage contracts, consulting opportunities, and Client relationships. Involved in each of our Clients' projects. Deliver training and hands-on-workshops at professional data science conferences across the United States.

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Well-Versed in Open-Source Programming Languages and Proprietary Programming Languages

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Well-versed in Open-Source languages including Python, R, JavaScript (React.js), and SQL

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Experience working in proprietary languages and products including SAS, Google Earth Engine, and ArcGIS

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Develop responsive applications with scalable API frameworks (FastAPI, Flask, Django, and Node.js)

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Create full-stack applications and conduct analysis in programming languages tailored to Clients' needs

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Experienced in Data Engineering, Data Pipeline Development, and Data Processing

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Engineer high-speed pipelines into cloud storage services such as Amazon S3 and Google Cloud Storage

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Process unstructured images, videos, audio files, and text sources as inputs for models and algorithms

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Query data inside of structured relational databases and import semi-structured delimited files

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Experienced in spatiotemporal data formats, file types, tiling providers, and storage services

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Implementing Scalable, Data-Driven Analysis using Python, R, and SAS​

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Assist Clients develop optimized workflows that scale well for big data in Python, R, and SAS

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Perform programming language conversions between Python, R, and SAS

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Develop training seminars and hands-on-workshops for Python, R, and SAS users

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Helping Clients Chart their Machine Learning Roadmaps from Model Training to Deployment​​

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Leverage Statistical Analysis, Machine Learning, Deep Learning, Generative AI, and Forecasting for Clients​

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Help organizations navigate complexities of supervised, semi-supervised, and unsupervised ML

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Train, fine-tune, optimize, and determine best-performing models and algorithms for Clients

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Program in Python, R, and SAS for Statistical Modeling and Machine Learning projects

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Developing Responsive and Interactive Full-Stack Web Applications​

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Experienced in React.js for developing sleek and professional front-end interfaces

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Integrate server-side data analysis, requests, and data querying using Python's API frameworks

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Create interactive web applications and dashboards that are tailored to Clients' needs

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Adjunct Faculty and Research Scientist

Responsible for designing and delivering curriculum for certain graduate-level courses in the Big Data Analytics program at San Diego State University. Responsibilities include building courses that teach practical, industry-expected skills in data science, presenting engaging lectures, and selecting topics from several areas in data science ranging from Python programming, R programming, machine learning, statistical analysis, GIS analysis, database structuring, and application development to immerse students in applied fields of study.

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Fall 2023: Advanced Special Topics in Big Data Analytics (BDA 696)

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Spring 2024: Machine Learning Engineering (BDA 602) and Spatiotemporal Analysis and Modeling (STAT 596)

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Fall 2024: Advanced Special Topics in Big Data Analytics (BDA 696) and Applied Multivariate Statistics (STAT 520)

Data Scientist and Researcher

Oversaw and coordinated research into the development of supervised and generative neural networks (deep learning models) for unstructured image and video data. Particular emphasis on visualizing spatial data that changes over time (spatiotemporal data) using Python, R, and Google Earth Engine. Designed interactive applications with front-end interfaces for viewing, querying, and analyzing climatological, geological, and environmental data.

Implemented relational databases for efficiently storing and querying downloaded climate image data, giving structure to unstructured datasets through SQL integrations in Python for GIS analysis. Designed data pipelines to optimize loading of Big Data into models for training and prediction. Processed historical and real-time Big Data from the U.S. Census Bureau, NOAA, and Google Earth Engine for visualization, analysis, and modeling.

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Developed a series of R statistical programming videos for reporting descriptive statistics, visualizations, and performing array operations taking advantage of R's vectorization and built-in functions. Training videos are posted publicly on YouTube, viewable by clicking here.

Instructor and Graduate Teaching Associate

Instructor at San Diego State University for Introductory Statistics: STAT-250. Trained students in using Microsoft Excel for data extraction, cleaning, exploratory analysis, visualizing variables, building linear regression models, conducting parametric statistical tests to evaluate claims, and drawing conclusions from results. Discussed the assumptions and limitations of popular parametric tests and regression models, including when to use certain statistical tests over others.

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Developed presentations and hands-on activities to engage students in weekly lectures. Received overwhelmingly positive anonymous reviews from students, available upon request.