Machine-Learning

Exercise and Project Responses

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Data Science Alumni Speaker (July 10) - Extra Credit

On Friday, July 10, I attended the third Data Science alumni speaker series about Tommy Jones from in-Q-Tel. in-Q-Tel is a firm that invests in startups, so Tommy examines the startups’ technology and determines how valuable they may be to the intelligence community. He also volunteers with Data Community DC, which sets up meetups and networking for data science professionals in the area. As part of Tommy’s Ph.D. research, he also works on developing statistical models for natural language processing (NLP) and open-source R packages.

Tommy was in the Marine Corps. prior to starting college at Webster University, where he pursued an international relations major because of its connection to his military experience. Shortly thereafter, Tommy transferred to William & Mary and decided to double-major in economics. After falling in love with economics, he decided to move towards tech and statistics because of its applications to econometrics. Consequently, he dropped his international relations major and pursued a math minor alongside his degree in economics. During his time at William & Mary, he interned with the Global Research Institute, which introduced him to extracurricular research. This experience revealed to him the importance of developing programming skills. I thought it was interesting how Tommy said that he’s seen this skill split people into the haves and have-nots in the workplace.

Because of Tommy’s research experience in school, he decided to pursue research in his career and interned as a research assistant at the Federal Reserve after graduation. In this position, Tommy participated in economic analysis and maintained the databases for economists and fellow research assistants to use in their research. After interning with the Federal Reserve, Tommy got his masters at George Mason University and interned with a machine-learning startup. Having had a lot of experience with statistics through his math minor and previous work experience, Tommy believes that machine learning provides a great opportunity to meaningfully apply statistical skills. He worked for several startups prior to arriving at in-Q-Tel in 2017, which gave him the opportunity to work in a broad range of industries.

Tommy believes that computer science and statistics are two of the most important job skills and, combined, they are even more valuable. He also believes that it is vital to be knowledgeable about the humanities and world events so that you can take your tech skills and apply them in meaningful ways. Tommy also said that he sees the use of NLP as a rising trend in the industry. He thinks that the previous hindrance to the diffusion of NLP tools was that they were very niche and required a lot of programming knowledge, but now he sees the technology becoming much more user-friendly. Creating more access to these tools is the impetus behind his work in developing open-source packages.