On April 23, 2018, I enrolled in General Assembly’s Data Science course, a full-time immersion program designed to teach programming languages, data analysis techniques, and machine learning skills in 12 weeks.

On April 23, 2018, I enrolled in General Assembly’s Data Science course, a full-time immersion program designed to teach programming languages, data analysis techniques, and machine learning skills in 12 weeks. On the first day, I was writing code in Python, parsing out a dictionary full of Pokemon characteristics, and wondering if I had made a huge mistake.

I started off my career as a Paralegal for the Violent and Organized Crime Unit of the U.S. Attorney’s Office for the Southern District of New York. I knew from the first day I stepped inside of that dilapitated office, I had found my people and my purpose. For the next three and a half years, I worked on a wide range of cases related to gang violence, drug trafficking, human trafficking, and securities fraud, helping Assistant U.S. Attorneys (AUSAs) prepare for trial. I later left that office to join the New Jersey Attorney General’s Office where I continued my investigative work as a Detective for the Public Corruption Unit.

The decision to enroll in a data science bootcamp started the year prior when I was working at a consulting firm tasked with the five-year, court-appointed monitorship of HSBC. I frequently found myself on teams responsible for investigating transaction-monitoring alerts (given my investigations background) but was routinely passed over for more analytics-based projects in favor of someone with more advanced skills. I knew what I wanted the data to bear out, I just didn’t know how to do it.

Frustrated with the limitations of my skillset, I initially took one-off Excel courses to boost my understanding of pivot tables and functions but did not feel satisfied with the results. While Excel is a powerful tool and can be useful in some types of analyses, it cannot compute on datasets larger than a million rows and cannot identify the kind of insights machine learning packages can. I realized if I wanted to keep moving forward in my career as an investigator, to be able to interrogate large datasets, to identify unprecedented insights, I needed to invest in upping my tech skills.

And that’s the path that led me to writing for-loops over a dictionary of full of Pokemon names, gym locations, and combat techniques. Over the course of the next 12 weeks, I would learn even more about data mining, data enrichment, natural language processing, data visualization, and many different machine learning packages.

This blog, The Data Sleuth, was inspired by my experiences in both investigative work as well as data science. It is a collection of my work that I began in my course and that I have continued to refine in the following weeks and months post-graduation. Feel free to read through the blog posts which are usually shorter topical pieces or have a looked at my portfolio in the ‘Projects’ section, where I go more in depth into the methodology I followed for that particular project. Should you have any questions related to the topics I write about, any code associated with my projects, or just want to chat about my experience in the coding bootcamp, do not hesitate to reach out via email by clicking on the envelope icon on the left. I look forward to hearing from you!

Welcome to The Data Sleuth.