Robert Munoz - Analayst,

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Work Background

Berkeley LabSystems Analyst - Affiliate

Mar. 2021 - Mar. 2022Remote due to COVID*Evaluated bug tracking program real-time data to identify and improve upon program areas by evidence-based decision-making and data analytics, resulting in a 50% increase in automation potential. *Conducted study on new software program options through a comprehensive evaluation of TCO, adaptability, and automation capabilities for delivery and benefit of services to software developers and users. *Created a strong case for a new software management system by preparing program findings and recommendations using reporting tools including Python, Tableau, MS Word, Excel, PowerPoint, and other SaaS AI Platforms resulting in new software procurement and implementation.

U.S. Department of Veterans AffairsVeterans Readiness and Employment Program Participant - Data Science and Analytics

Dec. 2019 - Mar. 2021Oakland, California, United StatesTraining and practical hands-on work experience. Data Science Immersive Training -Covers key elements in the data science toolkit including Git, SQL, regression and classification models, natural language processing, machine learning, and data visualization

General AssemblyData Science Immersive

Dec. 2019 - Mar. 2020San Francisco Bay AreaGeneral Assembly's Data Science Immersive Course is a full-time 12 week (480+ hrs) course that prepares professionals for roles in Data Analytics and Data Science. Course covers key elements in the data science toolkit including Python, Git, SQL, regression and classification models, NLP, machine learning, and data visualization. Projects undertaken during the course included: *Analyzing characteristics of Reddit posts - NLP project to identify what characteristics make for a successful Reddit post, using data accessed through the Reddit API. For my project, two subreddit posts were collected: r/49ers and r/NFL Using a NLP. A classifier was trained on which subreddit a given post came from. A successful distinction was made with ~75% accuracy. *Predicting house prices - Built a linear regression model to predict sale prices of homes in Ames, IA from a feature set of over 70 features. Goal is to help consumers make more informed financial decisions about their homes through a complex and proprietary algorithm that incorporates millions of data points. We determined features that correlate best with house price and use them in our predictive model. R2 value determined that 89% of the variability in home pricing is explained by the model. *Use of Google Street View as Baseline for FEMA Damage Assessment (Team concept project) Using Python, determined the economic impact of local home disasters through Sklearn, Keras and TensorFlow to summarize pre and post-disaster information on the property of interest. Provide damage assessment input in addition to relevant information about the level of damage to the structures and pre-event photos of the assessed structure. *Exoplanet Discovery (Personal concept project) Utilized Random Forest and TensorFlow models and trained a convolutional neural network to classify Kepler Threshold Crossing Events (TCEs) as either "planet" or "not planet", achieved a >97% confidence level that the input TCE is a planet.

Complete Coach WorksMechanic Helper

Aug. 2018 - Nov. 2019Alameda, California, United States*Reduced time by 50% to route, install and test Facebook Shuttle Bus LED displays and controls. *Inspected and tested machinery/components to diagnose issues, recognize defects *Managed transportation bus wheelchair ramp refurbishment program as electro/mechanical repair technician with improved efficiency and reduction in labor hours. *Developed a keen sense for customer service and becoming customer focused.

EBMUDAssociate Engineer

Nov. 1999 - Mar. 2013Oakland, California, United StatesLead Project Facilitator, Trainer, and Developer for Water and Power systems maintenance and reliability program. • Led the development of a new maintenance program for a $700 million construction project in collaboration with numerous internal and external stakeholders, producing a program that was successful, affordable, dependable, and safe, with a reduction between 20% and 70% of routine maintenance. • Conducted independent research and in-depth study of the current maintenance program for multiple facilities by offering professional advice and technical support on issues relating to suggested policies and procedural modifications resulting in a substantial impact on data intake and employee work processing to address problematic maintenance issues. • Trained management and workforce stakeholders through presentations and training materials by targeting specific topics and audiences during one-on-one and group sessions, leading to enhanced comprehension, improved morale, and informed decision making.

ERIN Engineering and Research, Inc., a JENSEN HUGHES CompanySenior Engineer

Jan. 1998 - Jan. 2001Walnut Creek, California, United States- Reliability-centered Maintenance Project analyst for power industry clients which included Failure Modes, Effects, and Criticality analysis and maintenance task recommendations - Interpreted and utilized system process information by extensive use of technical manuals, Operating and Maintenance Manuals, As-built design and process drawings, and database files - Extensive travel across the western United States for program delivery to power industry clients which included introductory meetings, multidisciplinary interview meetings, site walk-thru, technical training, final presentations, project summary to managers, supervisors, and multidisciplinary teams