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MSDS Alumni Profile: Stavros Kontzias
Stavros Kontzias
Employment
Self-Employed, Data Scientist/Engineer (Washington DC Metro Area)
Education
M.S. in Data Science 2024, University of Virginia
B.B.A. in Finance and Computer Information Systems 2018, James Madison University
Q: Walk us through what you did at work today.
The day began with me opening up Jupyter Notebook, which is an indispensable tool in my daily workflow. I kicked off by reviewing the logs from the overnight data pipeline runs to ensure there were no issues that might have impacted our data ingestion processes.
Next, I had a meeting with stakeholders to discuss and refine their data requirements for an upcoming project. This step is crucial as it ensures that our data models and pipelines are aligned with the business objectives and user needs.
Following the meeting, I dove into some data engineering tasks. This involved querying large datasets to extract and transform data, moving it across different environments securely and efficiently. I also spent a significant portion of the day working on fine-tuning our large language models (LLMs), which are central to a current project I am supporting regarding a semantic search capability. This involves a mix of parameter tuning, training, and validation to ensure our models perform optimally
In the afternoon, I led my team of engineers in a brainstorming session to tackle some challenges we’ve been facing with our data pipelines and new LLM model that was just released. We discussed various strategies, including optimizing our model architecture and improving our data architecture.
The day wrapped up with me documenting our progress and findings, and planning the next steps for our projects. As always, staying ahead in the rapidly evolving field of data science and engineering requires continuous learning and adaptation, which I find incredibly exciting and rewarding.
Q: What did you learn in the M.S. in Data Science (MSDS) program that you have found most useful in your career so far? And what do you wish you had learned?
The MSDS program has been instrumental in shaping my career as a Data Scientist and Data Engineer. While the mathematical foundations, programming skills, and various analytical techniques we learned have been incredibly useful, the most valuable lesson was how to think like a data scientist. The program emphasized the importance of formulating the right questions and approaching problems with a data-driven mindset, which has been crucial in my role where I lead a team of engineers and work with stakeholders to elicit requirements.
However, I do wish we had learned more about Spark for parallel processing. Given the scale of data we handle in our projects, having a deeper understanding of Spark would have been extremely beneficial for optimizing our data processing workflows.
Q: How did the MSDS Capstone project prepare you for your current work?
The Capstone project was pivotal in preparing me for my current role. It involved using large language models (LLMs) in a search function, a project closely related to what I am working on now. This hands-on experience with LLMs provided me with practical skills in implementing and fine-tuning these models to enhance search functionalities. It also gave me valuable insights into the challenges and best practices in working with advanced machine learning models, which I apply daily as I lead a team of engineers in developing and optimizing LLM models for various applications.
Q: Were there specific classes, projects, or professors that you found particularly influential in preparing you for your career?
Every class, project, and professor in the MSDS program played a significant role in preparing me for my career. Each element contributed to my understanding of the field in a unique and meaningful way. The diverse curriculum and varied projects provided a comprehensive foundation in data science, equipping me with the necessary skills and knowledge to excel in my role. The professors, with their vast expertise and insights, were instrumental in guiding me through complex concepts and real-world applications, ensuring I was well-prepared for the challenges of a career in data science and engineering.
Q: How do you perceive the impact of your MSDS degree on your career advancement and opportunities?
Having been in the field of data science prior to pursuing the MSDS degree, the program provided the accreditation and confidence I needed to take a significant step in my career. It enabled me to start my own company where I provide data analytics services. The degree not only validated my expertise but also opened up numerous opportunities by enhancing my credentials and demonstrating my commitment to professional growth. This has been instrumental in gaining the trust of clients and stakeholders, ultimately driving the success of my entrepreneurial venture.
Q: As you look ahead, where do you envision yourself professionally in the next 5-10 years? Are there specific career goals, projects, or milestones you aspire to achieve in the coming years?
In the next 5-10 years, I envision myself scaling up my company, expanding our reach, and providing innovative data analytics solutions to a broader range of clients (currently support primarily the federal government). One of my goals is to lead large-scale projects that drive significant impact and help organizations harness the full potential of their data. And who knows, maybe a Ph.D. in Data Science is next on the horizon!
