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AI Researcher Loves Working With Messy Data


Name: Victor Murcia (he/him)

PhD: Materials Science and Engineering, Washington State University, 2022



What was your main area of research?

I developed a quantitatively accurate tensor-based framework developed from a combination of first principle calculations, custom machine learning algorithms and advanced synchrotron x-ray techniques. The optical models produced from my approach allow one to extract quantities like molecular orientation in complicated systems like polymer blends used in various organic electronic applications.



What is your current job?

I am a Data Scientist/AI Researcher for the U.S. Department of Veterans Affairs [Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) and National Artificial Intelligence Institute (NAII)] in Jersey City, New Jersey.


I use a variety of statistical and AI methods (Machine Learning [ML], Computer Vision, and Natural Language Processing) to assist in a variety of healthcare applications. I maintain and create databases, construct ETL pipelines, train, optimize, deploy, and monitor ML models, and communicate my findings via conference presentations and publications.


I am one of those weird people that loves working with messy data. Healthcare data is extremely messy, of large dimensionality, multimodal, and absolutely massive. Working in this field requires me to leverage the full extent of my technical skill set across a variety of disciplines. This in turn helps me grow given the wide array of problems that I have to solve.



How did you find this position? What were the career steps you took to get to where you are now? 

I found the position through LinkedIn. 


PhD graduate ➡️ Data Scientist/AI Researcher



Why did you decide to not pursue a career in academia? 

I knew I wasn't going to stay in academia before I started my PhD. I knew I loved research, but I was also well aware that there is limited availability for positions as a professor. I was also aware of how poorly-paid and stressful the vast majority of postdoc positions are. Therefore, I knew from the beginning of my journey that I'd end up in industry doing some sort of R&D. 



What advice do you have for someone getting their PhD and looking to pursue a career outside of academia?

  1. Check job postings at least once a year in the areas and positions you'd be interested in pursuing. This will give you an idea of what skills are important to prospective employers. 

  2. Start interviewing as early as you can. This will serve as a barometer of where you stand with respect to your peers.

  3. For data science, I highly recommend that you build a portfolio with interactive projects. Recruiters and hiring managers are far more likely to remember you if you provide them with a project that they can interact with. The projects don't necessarily have to be providing "business impact". In my case, my projects were centered on things that I thought were interesting. 

    1. For instance, one of the projects I showcased that helped me land an interview and ultimately a job offer involved an application that used natural language processing (NLP) to perform a 10-axis sentiment analysis on a book from ProjectGutenberg. The application would query for the book, split into sections, carry out a variety of NLP tasks, and then provide a variety of information about the book like how does the tone change over the course of the book. 



Are there any components of your identity you would like to share, including how they have impacted your journey?

I'm an immigrant from Honduras. I'm the first person in my family to ever acquire a PhD. Fortunately, I had amazing mentors throughout my journey that helped me navigate the educational system because I don't think I would've made it otherwise.

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