Christine Egan

Tampa, Florida, USA christine.egan42@gmail.com

My expertise lies in applying artificial intelligence to optimize solutions and achieve superior outcomes. I specialize in leveraging cutting-edge technologies and applying my aptitude for Python development to build expert systems and machine-learning pipelines that enhance insights. Using my background in linguistics and my knowledge of natural language processing, I reveal the hidden structures in unstructured data.

Experience

Senior Curriculum Developer

Flatiron School

I develop and maintain interactive data science curriculum on topics like Python, Data Analysis, Data Visualization, Dashboards, Web Scraping and APIs, Natural Language Processing, Artificial Intelligence, and Machine Learning.

October 2022 - Present

Data Scientist (Consultant)

GCOM Software

I conducted entity resolution for federal clients using Databricks and PySpark to link entities from millions of financial records. I also developed entity extraction engines using Python and spaCy to automate hotline complaint processing.

March 2022 - October 2022

Data Analyst (Consultant)

ASR Analytics

I developed an expert system using novel business rules for federal clients to identify synthetic ID scams and built Python pipelines for data processing. I conducted quantitative and behavioral analysis to provide actionable recommendations for synthetic ID detection methodology.

August 2021 - March 2022

Education

Flatiron School

Immersive Data Science Bootcamp
May 2020 - April 2021

Stony Brook University

Linguistics and Philosophy
January 2016 - May 2019

Technical Writing

Simple network diagram with labeled nodes and edges.
Social Network Analysis with Python and Network X: Part 1

A beginner’s guide to using Python’s NetworkX library to conduct social network analysis that introduces measures of centrality using a simple network example.

More complex network with nodes labeled as individuals in the network.
Social Network Analysis with Python and Network X: Part 2

Builds on "Social Network Analysis with Python and Network X: Part 1" by introducing a more complex network example, and exploring how this changes measures of centrality.

More complex network with nodes labeled as individuals in the network.
Social Network Analysis with Python and Network X: Part 3

Builds on "Social Network Analysis with Python and Network X: Part 2" by introducing a more complex network example, and exploring how this changes measures of centrality.

More complex network with nodes labeled as individuals in the network.
Social Network Analysis with Python and Network X: Part 4

Builds on "Social Network Analysis with Python and Network X: Part 3" by introducing a more complex network example, and exploring how this changes measures of centrality.