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Big Data, Data Mining, Machine Learning, Data Visualization, SQL, C#

Location:
Madison, Wisconsin, United States
Salary:
75-100k
Posted:
November 12, 2018

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Resume:

M a l c o l m C a l l i s

**** ********* ** #* *******, WI 53713

567-***-**** ac7n9m@r.postjobfree.com:ac7n9m@r.postjobfree.com

Skills

Big Data, Data Mining, Machine Learning, Data Visualization, SQL, LINQ, C#, MATLAB, Python, Genetic Algorithms, Neural Networks, Neuroevolution, Agile Software Development, Java, ASP.NET MVC, JavaScript, AJAX, GitHub, TortoiseSVN

Work Experience

Software Developer July 2016 – July 2018

Epic Systems Corporation

Designed, developed and tested a web-based information dashboard to help outpatient chief medical information officers, IT analysts and Epic trainers identify physicians at risk of burnout and provide targeted training recommendations

sCollected metrics on 130,000 physicians’ electronic health record system usage patterns

sUsed elastic net regression written in Python to determine how usage patterns affect physicians’ efficacy and sense of well-being

sUsed extensive caching, indexing and query optimization to reduce average web page request time from 4.5 to 1.8 seconds

sDesigned and implemented aesthetic and intuitive data visualizations

sWrote, oversaw, administered, and reflected on usability tests with customers

sTaught SQL database structure and C#/LINQ business logic codebase to new team members

sThe first six months after release resulted in an average savings of 2.4 minutes in EHR system per physician work day, saving 26,000 hours per week across the United States

Traveled to customer sites during Epic go-lives to support physician end users and get feedback on Epic’s training courses

Spearheaded project to generate post-implementation user satisfaction reports benchmarked across the Epic community

Presented a summary on Robert Martin’s book Clean Code and was a strong advocate for writing highly modularized, self-documenting code and repaying technical debt

Student Research Assistant April 2014 – May 2016

The Ohio State University Department of Biomedical Informatics

Developed a cancer simulation in Java to model the effects of administering different drug treatments

Wrote highly parallelized code which was executed on the Bucki Supercomputing Cluster

Animated results in a 3-dimensional visualization of tumor growth in MATLAB

Volunteer Summer 2015

Samerth Charitable Trust

Assisted in the construction of a 70,000 liter roof rainwater harvesting system for a rural school in Gaghador, India

Education

B.S. in Computer Science and Engineering May 2016

The Ohio State University

GPA: 3.9/4.0, Summa Cum Laude

Relevant Courses

Machine Learning, Data Mining, Neural Networks, Parallel Computing, Artificial Intelligence, Database Systems

Machine Learning Class Project

sPredicted the growth rate of in vitro cancer cells after being exposed to different experimental drug treatments

sFeatures used were based on genomic point mutations and the physicochemical structure of the test drugs

sResult: R^2 of .83 predictive effectiveness of drugs on unseen test data

Personal Projects

Neuroevolution Simulation

Creatures and food spawn in a 2D environment

Creatures’ behavior is controlled by a two layer feed forward neural network

Each neuron has a homologous pair of genes coding for the weights of synapses leading into the neuron

The creatures go through a process of meiosis and genetic recombination mimicking what occurs in nature

The synapse weights have a small chance of randomly mutating upon reproduction

The creatures then compete amongst themselves causing the least fit members of the species to die off and the strongest to proliferate, ensuring that the AI gradually get better the longer the simulation runs

Predicting Home Sale Prices Kaggle Competition

Challenge was to predict home sales prices based on 79 explanatory variables

Python, hyperparameter tuning, feature selection

Bagging ensemble method of multiple regression techniques

Predictions ranked in top 47 percent of Kaggle competitor submissions



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