My name is Javier Orraca and I drive business value for corporations and privately held businesses through data, predictive modeling, and empowering stakeholders with robust decision analytics.
My career includes over a decade of consulting, data analysis, financial modeling, and data science for Ernst & Young (EY), Pacific Gas & Electric (PG&E), KPMG, and Health Net (a Centene Corporation subsidiary). I had a vision of providing more value to business organizations than what my M&A work allowed for, so I began to explore and learn how to apply regressions, advanced analytics, and machine learning for data-driven decision making.
Finding a new passion in analytics and data science, I pursued a Business Analytics graduate degree at the University of California, Irvine, and graduated in 2019. Throughout my graduate program, I leveraged my data and financial modeling experiences to help financial services firms, advertising agencies, and retail businesses. Throughout my masters program, I developed a commercial AI product for financial modelers and since graduating, I have been at Health Net as a Data Scientist III. My core responsibilities include the development of machine learning and AI models for strategic insights.
I’m humbled to be part of the data science community, continuously learning, networking, and sharing best practices around programming, advanced statistical analyses, data visualizations, machine learning, and data analytics. I launched Scatter Podcast to share career tips and insights from data science leaders that I interview. Check out the dedicated Scatter Podcast page on this site to listen to recent episodes on the embedded player, or subscribe via your platform of choice!
Programming & Analytics Skills
- R: RStudio, R Markdown, flexdashboards, R Shiny, plyr, dplyr, ggplot2, reshape2, sqldf, blogdown, Plotly, gganimate, lm / glm, Keras, TensorFlow, data.table, ReadR, vroom, broom, officeR, Facebook Prophet, and more R packages
- Python: Pandas, NumPy, scikit-learn, RStudio (via R Markdown + reticulate), voila, PySpark, Google Colab, matplotlib, seaborn, Plotly, PyTorch, and more Python libraries
- Other Analytics & Programming Tools: Tableau, SQL, JupyterLab, Jupyter Notebooks, Microsoft Dynamics / D365, Microsoft PowerBI, Alteryx, Linux (Ubuntu), NetBase, IBM Watson Cloud Studio, MegaStat, SAP Business Objects, SAP Analysis for Excel, Adaptive Insights, SAS, Hugo, Netlify
- Microsoft Excel: pivot tables, nested IF statements, INDEX / MATCH functions, VLOOKUP / HLOOKUP functions, Solver (for optimization and simulations)
- Microsoft Access: data pipelines, data manipulation, ODBC integration, query design (joins, crosstab, make-table, etc.), reports, forms, macros
- Scatter Podcast mention on Forbes: https://forbes.com/how-to-get-your-data-scientist-career-started
- Scatter Podcast on UC Irvine News: https://merage.uci.edu/news/2019/06/scatterpodcast
- Orange County Predictive Modeling Hackathon Winner: https://twitter.com/oc_rug/status/oc-r-users-group-hackathon-best-model
- UC Irvine Student Profile: https://merage.uci.edu/programs/masters/master-science-business-analytics
I am not a web developer but I created this website using the R programming language, RStudio, blogdown, and Hugo. My site renders in less than 80ms and I’m hosting it for free… It only cost me time and $15/year for the domain name. Open-source tools are fast, flexible, fun, and paving the future of analytics.
Web Resume: https://www.javierorraca.com/resume/