I offer full stack data science and ML engineering services, as a consultant or hourly contractor.

In the world of data-centric projects, people tend to specialize in either pure data science, ML research, ML operations, cloud infrastructure, or general backend software engineering. I bring the most value to clients by combining perspectives from all layers of the data stack. Whether you’re looking to get started with exploratory data analysis, or find yourself ready for deployment and operations, I can help.

I have a Masters in CS from the University of Wisconsin-Madison, where I specialized in Natural Language Process (NLP). I previously worked as a software engineer at before going independent.

Reach me at

TopTal Princeton Equity Group Channel Science Terms of Service; Didn't Read

Research and Discovery

How much data will you need? How long will it take to build? Will it scale? Big unknowns can be paralyzing for startups. Through prototyping, rapid literature reviews, dataset analysis, and an intuition built over many years, I will guide you toward clarity as quickly as possible.

Applied Machine Learning

Data science in the real world requires domain expertise, creative thinking, and a skeptical mindset. I have direct experience solving real problems with ML in the following domains:

  • Natural Language Processing (NLP)
  • Audio ML, Music Information Retrieval
  • Signal Processing
  • Reinforcement Learning

Software Engineering

I have over a decade of experience managing complexity through thoughtful software design. This includes integration with cloud platforms, distributed systems, deployments and operations, and leading teams of developers.

I work primarily in Python. I use whatever libraries are best suited to solve the problem at hand, which often includes PyTorch, tensorflow, Scikit-learn, pandas, spacy, SciPy, and cloud offerings from AWS or GCP.

Have some data and a problem to solve?

Let's chat!