Brendan Aleksivich

Data is great. Data with a well defined question to answer in a purposeful use case - that's beautiful. I'm a data scientist, currently in the defense domain, who has a thirst for answers to the hard questions and solving the hard problems. From ad-hoc analyses to complete analytical systems, my experience runs the gamut. I've been fortunate enough to work on some very impactful projects that drive real decisions, and real change. With a background in Mechanical Engineering and professional experience in data science, along with a soon to be completed Masters in Computer Science, and am a well rounded data scientist who has an aptitude for applying engineering knowledge to real world applications. My bread and butter is Python and the core data science libraries (Pandas, Numpy, Tensorflow, SciKit Learn, etc.), but I have have experience developing with OOP languages, namely Java and C#. I most often find myself enjoying reinforcement learning and agent-in-the-loop data science applications. I'm a strong proponent that there are often more efficient and effective ways to complete tasks that humans are incapable of identifying on their own. Seeing an AI agent develop a certain strategy or set of rules that was previously incomprehensible to a human is fascinating and something I continue to pursue in my projects. I also have a penchant for cloud infrastructure and computing. Microservice architectures are exceptionally powerful and flexible and I beleive should be the crux of development for data scientists, especially as data continues to grow in size and complexity. In my spare time, I enjoy applying analytics and visualization to fun personal projects like fantasy sports or stock market analysis. I also enjoy getting behind a lens and doing landscape photography - even better if it's at night.