- Assists solution architects in designing and developing solutions for cloud customers.- Performs basic system administration tasks in Linux environment.- Researched and proposed an algorithm for a time-series based machine learning solution.- Experience writing PySpark code to process and explore datasets.- Develops Jupyter Notebooks for visualization and communicating results of exploratory data analysis.- Designed cloud-native data lake with associated data pipelines to support machine learning and analytics use cases.- Experience building Docker images for various applications.- Built container-based Kafka cluster for use in development environment.

Supported the data infrastructure needs of a marketing analytics team. I owned the maintenance of the public datasets and designed solutions for both relational and distributed systems.-Collected requirements, designed, and built Postgres data warehouse for multiple data sources.-Developed Extract-Transform-Load (ETL) pipelines to retrieve external data, process, and store in Postgres.-Experience processing a variety of data types such as raw text, structured files, XML, JSON, and REST APIs.-Worked with customers from other teams to create denormalized tables for specific use cases.-Maintained and debugged an automated web scraper.-Advised the Hadoop team regarding ETL pipelines to the distributed platform.-Experience writing Spark code to process large datasets in the Hadoop ecosystem (PySpark, Impala).-Provided data dictionaries and code documentation to team and maintained the Github repo.

As a Data Engineer, my role is to support various business units by building tables and clean data sets for reporting and analytics. We use SQL Server and as a result my main tool is SSMS and TSQL. On occasion, I'll use Python to develop solutions for problems where appropriate.The main project I have been involved with during my tenure is acting as the technical lead for the provider portion of the QNXT migration task. My responsibilities include communicating with both the business SME's and Cognizant consultants for requirement gathering. I then write stored procedures to generate conversion data sets and communicate the results to the key decision makers.I also have experience writing scripts to report on Coordinated Care Organization (CCO) metrics. In addition, I have recently learned how to use the Excel Data Models for performing analysis on my results and easily communicating them to internal customers.

My primary role was to assist senior data science team members by building data sets for future machine learning models. In addition, I worked on a few small projects.-Feature Engineering/Data Scrubbing: Wrote SQL scripts to group claims data into datasets of various events such as hospital admissions, emergency dept visits, and outpatient visits. Certain components of this project required Python development as SQL was not the appropriate tool.-Machine Learning Engineering: Developed a Self-Organizing Map (SOM) for a possible imputation use case. The model was built from scratch using Python as there were no third party libraries to meet our needs.-Statistical Analysis: Wrote SQL scripts to pull data for an analysis of inpatient mental health utilization. The customer worked best with Excel so I built a workbook of interactive histograms and charts.-Data Gathering/Retrieval: Wrote Python scripts to scrape Leapfrog hospital quality ratings from the web in addition to extracting provider data from the NPPES NPI Registry API.

The focus of teuscher.:Lab is to study next-generation computing models and architectures. As part of the Undergraduate Research and Mentorship Program (URMP), my education has been project-based as opposed to classroom-based. Under the mentorship of a Phd student, I developed and trained a single-layer artificial neural network to generate sparse codes for classifying images of hand written digits. The project was developed in Python. In addition to studying the underlying theory of machine learning and neural networks, I am also learning general software development best practices with regards to coding and debugging in Python.My next project will focus on video processing and testing the limits of the hardware processing such algorithms. In addition, I will be working on deep learning problems and developing GPU programming skills.http://www.teuscher-lab.com/

Actuarial Exams: P, FM, MFE, FAP IA, and all VEE's

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