I'm a senior data scientist with a mathematics background and graduate research in neural networks, with production experience in ML, computer vision, NLP, and AI systems. I'm looking for a senior individual contributor role where I work across the company to understand what people are trying to answer and whether the data exists to answer it, with room to mentor junior data scientists. I'd like to do that work at an organization whose mission involves doing some good in the world; a nonprofit, a progressive organization, or work on the electrical grid.
Category:Data
Experience: 10+ years
Open to: On-site, Hybrid, Remote
Locations: Minneapolis/St Paul Area; Greater Minnesota; Chicago Area; Detroit Area; Portland, Oregon Area; Raleigh/Durham Area; Madison, WI Area; Rochester, MN Area
Timezones: US Central, US Mountain, US Pacific
Employment types: Full-time, Part-time, Contract
Contribution types: Individual Contributor, People Manager
Status: Actively looking
Expertise: Data Science, Machine Learning, NLP, Computer Vision, AI
In their words
How would you describe your ideal next role?
A senior individual contributor role where I work across the company with product, engineering, and leadership to understand what issues not be solved. I'd also like to mentor junior data scientists.
How would you describe your professional background?
I studied mathematics at Wayne State, then did graduate research in neural networks and evolutionary computation at Portland State. I spent over 25 years in software engineering before moving into data science, which was the natural place to land given the math and programming background. Since then my work has spanned production ML, computer vision, NLP, and AI systems
How would you describe your ideal next employer?
I'm looking for an organization whose mission involves doing some good in the world; nonprofits, progressive organizations, or work on the electrical grid. Size matters less to me than whether the work is technically serious and whether data science is used because the problem calls for it, not because it's expected. I'd want a culture where people across functions talk to each other and where honest assessments of what the data can and can't support are welcome.
Anything else to add?
I'm willing to relocate
