Engineer Technical Support

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Erenis Lemus

******.*****@*****.***, Los Angeles, CA Summary

Experienced engineer with a proven track record interfacing with large cross-functional teams on new product development, from design conceptualization, to experimental design and analysis, material property testing, and competitor analysis and benchmarking. Capable of tackling challenging problems for business needs in a dynamic, fast evolving environment and seeing them through from start to finish. Skills

Technical skills: Python SQL Matlab VBA Ladder Logic JMP Tableau Sisense Excel AutoCAD

Research skills: Data analysis experimental design statistical analysis six-sigma heat- transfer analysis particle tracking analysis image analysis optimization methods mathematics physics

Soft skills: Written and interpersonal communications skills creativity administrative roles

technical research results driven presentation skills initiative fluent in Spanish

Experience

Self-Employed, SOS Academic May 2017 – Present

Tutoring, Los Angeles CA

• Help students improve their grades through one-on-one & group tutoring.

• Running marketing campaigns to gain new customers.

• Using Google analytics to track website data on www.sos-academic.com Applications Engineer, Materia Inc. July 2014 – April 2017 R&D group, Pasadena CA

• Lead and managed JMP-SAS statistical software users group to ensure proper use of technology which included but was not limited to discussing the use of unsupervised versus supervised models.

• Designed experiments which reduced product material and labor complexity in R&D. Design of experiments (DOE’s) is a statistical method of efficiently approaching complex problems in R&D.

• Analyzed data generated by the DOE’s to optimize product properties. This usually involved supervised learning in which we found relationships between variables through ANOVA modeling.

• Wrote VBA script to automate data extraction from QC reports. This was all done on excel spreadsheets.

• Provided technical support to our business development team for marketing needs.

• Created heat transfer models on excel to help understand product performance under simulated environments. The analysis helped in product marketing

• Created customized data visualizations using Sisense for business needs. This included uploading data onto the ElastiCube, which is Sisense’s database, and building customized dashboards by integrating Javascript code into the available graphs and visualizations within the software.

• Assessed two Business Intelligence software, tableau and Sisense, for use in our company. Internship – Data Science, Helynx Nov. 2015 – Feb. 2016 R&D group, Idealab Pasadena CA

• Worked on predicting patient illness based on healthcare data with a machine learning algorithm. Page 2

• I worked with a deep belief network written in python from the theano library. This is a form of unsupervised learning. I looked at how the parameters affected the performance metrics and attempted to optimize them.

Undergraduate Researcher, Center for Energy Efficient Material Nov. 2013 – June 2014 Moskovits Research Group, Santa Barbara CA

• Fabricated an artificial photosynthetic device using surface plasmons. Undergraduate Researcher, Massachusetts Institute of Technology June 2013 – Aug. 2013 Stocker lab, Cambridge MA

• Completed a research project on tracking physical interactions via microscopy between two micro- organisms to predict optimal environmental conditions for interaction. Video recordings were taken of the micro-organism interacting under multiple environmental conditions. The videos were then analyzed using Matlab to track frequency of particle interactions. Undergraduate Researcher, University of California Santa Barbara Oct. 2011 – June 2013 Fygenson Lab, Santa Barbara CA

• Created a system for confirming attachment of two organisms using nanoparticle tracking analysis.

• Analyzed particle morphology using nanoparticle tracking analysis. Undergraduate Researcher, University of Minnesota June 2011 – Sep. 2011 St Anthony Falls Laboratory, Minneapolis MN

• Analyzed images via Matlab to calculate the average frontal area of seedlings.

• Used JMP-SAS software to analyze plant growth related parameters with frontal area and flexibility of seedlings.

Education

• Predictive Modeling and Analytics Competition (2017), Kaggle

• SQL Course Completion (2017), Codeacademy.

• Computational Physics Research (2016), University of California, Los Angeles.

• Python Course Completion (2014), Learn Python The Hard Way & Codeacademy.

• B.S. Physics (2014), University of California, Santa Barbara. Conference Proceedings

• Erenis Lemus & Steve Smriga, Characterization of Chemotaxis Cluster Experiments, SACNAS National Conference, San Antonio TX, 2013.

• Erenis Lemus & Steve Smriga, Characterization of Chemotaxis Cluster Experiments, MIT Summer Research Poster Session, Cambridge MA, 2013.

• Erenis Lemus & Deborah Fygenson, Mass Standards for Nanometrology: Method to enable confirmation of binding experiments, URCA Poster Presentation, Santa Barbaram, 2013.

• Erenis Lemus & Deborah Fygenson, Making Bicelles to Increase Binding Affinity of Glycolipid Decoys to Respiratory Pathogens, UCSB Undergraduate Research Colloquium, Santa Barbara, 2012.

• Erenis Lemus & Deborah Fygenson, Making Bicelles to Increase Binding Affinity of Glycolipid Decoys to Respiratory Pathogens, McNair Summer Colloquium, Santa Barbara, 2012.

• Erenis Lemus, A. Daley, L. Kui, D. Dalbotten, Frontal Area and Stem Flexibility of Cottonwood and Tamarisk, NCED Summer Colloquium, Minneapolis MN, 2011. Page 3

References furnished upon request

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