I will be working with the Advanced Analytics group in the Digital Transformation Organization, using emerging technologies to streamline business processes at Unum. I have already learned so much in the past 3 days, and I can't wait to see what is next!

Key Skills: Account based marketing, Salesforce API, programming and process automation, complex SQL queries, Azure Dev Ops, Google Cloud, data visualization, machine learning· Key Contribution: Developed and implemented Fuzzy Matching algorithm improvements which increased ac- curate company name matches by 10%, allowing more leads to be sent to sales representatives

Independent research which included the development of analytical image modeling code written in Python to characterize the dust tails of comets. Use of data science methods to analyze image data. Conversion of the existing code from Python 2.x to 3.x, and updated to include object-oriented programming techniques, new Gaussian modeling methods, and data adaptive algorithms. Used standard Python software packages, including Numpy, Scipy, and Matplotlib. Used statistical techniques in Python, including K-S testing, to test hypotheses and predict outcomes by determining the fitness-of-use of the models to the data. Used standard data tools and techniques to structure the resulting large data set to aid in analysis and interpretation of the results.Participated in the development of a data pipeline to automatically process astronomical image data on a nightly basis, so that the data could be used to find potentially hazardous asteroids and comets. This project has involved database development, database management, quality assurance, and machine learning (selection of training data, vetting of algorithm).Co-lead of Comet Working Group, tasked with ensuring that comets could be detected and characterized by the NEO Surveyor spacecraft, as tasked by NASA's Planetary Defense Coordination Office. Development of novel comet modeling algorithms to generate synthetic images to predict the effectiveness of the NEO Surveyor mission. Used statistical techniques in Python, including K-S testing, to test hypotheses and predict outcomes by determining the fitness-of-use of the models to the data. Used standard data tools and techniques to structure the resulting large data set to aid in analysis and interpretation of the results.

Developed computer code in Python to analyze infrared comet image data. Designing and developing of data analytics code to build models of comet tails to compare to actual data in a semi-automated manner, allowing data to be analyzed faster. Used standard Python analytical tools and data visualization tools including Numpy, Scipy, and Matplotlib. Developed algorithms and code to predict what the comet tails would look like given a variety of characteristics, then test that hypothesis by comparing to actual image data. Led the writing, and publication of, scientific papers in peer-reviewed journals.Participated in, and frequently led, tri-weekly quality assurance of infrared imaging data for the detection and characterization of asteroids and comets. Submitted results to the Minor Planet Center for further vetting and confirmation, leading to the discovery of hundreds of new asteroids and comets.Used numerous ground-based telescopes in a wide variety of locations to successfully collect astronomical data which was subsequently used in the publication of peer-reviewed scientific papers. Successfully completing an astronomical observing run requires a number of skills, including flexibility, stamina, persistence, identifying problematic issues, problem solving, data management, and the ability to incorporate changing conditions in to a plan on the fly.