Roban Hultman Kramer
holding my breath
AI Ethics at Indeed (2023-present)
Staff Data Scientist
AI Ethics team (2023-present)
We help all people get jobs.
Collaboration with teams across Indeed (the #1 job site in the world) to responsibly deploy technologies (like "AI" systems), evaluate the equity of automated decisions, and level the playing field for jobseekers facing bias and barriers.
I get to work on challenging analysis and inference problems related to evaluating model bias and performance, engineering design and implementation of infrastucture and self-service tools for other teams to use to evaluate and improve their models, and fundamental machine learning engineering / data science to figure out how to improve model fairness while preserving overall performance.
Machine Learning at Stripe (2015-2022)
Machine Learning Engineer
Responsible Machine Learning (2021-2022)
Founded Responsible Machine Learning at Stripe, working across multiple teams to decrease systemic barriers to economic participation and equalize access to the internet economy.
Payment Intelligence Optimizations team (2020-2021)
Optimization of how payments are presented to card networks to maximize authorization rates while controlling impacts on costs and fraud.
Machine Learning Engineering Manager
Merchant Forecasting team (2018-2020)
Founded and led the Merchant Forecasting team, focussing on merchant-level loss prevention.
Machine Learning Engineer
Transaction Fraud / Radar, Merchant Modeling (2015-2018)
Transaction fraud modeling (Stripe's Radar product), merchant fraud modeling, card testing detection.
Data Science at GLG (2012 - 2014)
Data Scientist
Gerson Lehrman Group / Hightable
Recommendation systems to match clients with expert consultants.
Astrophysics at ETH (2010-2012)
Zwicky Prize Postdoctoral Fellow
ETH Zürich (Swiss Federal Institute of Technology)
Study of the first stars and galaxies (via their ionization of the Intergalactic Medium) in the early universe using light from distant quasars.
Education
- PhD in Astronomy from Columbia University, 2009
- MA and MPhil in Astronomy, Columbia University, 2007
- BA in Astrophysics from Swarthmore College, 2003
Machine Learning and Software Engineering Experience
My experience includes: python (tensorflow, scipy, numpy, pandas, sklearn, jupyter), ruby, scala (spark, scalding), SQL, decision theory, machine learning, AI Ethics, Fairness in Machine Learning, Fainess Accountability and Transparency (FAccT), Bayesian inference (probabilistic data analysis), Markov chain Monte-Carlo algorithms (MCMC), data visualization (Matplotlib, d3, ggplot).
Machine Epistemology blog