We are open to hiring either a Machine Learning Engineer II, Economist (fresh PhD graduate) or a Senior Machine Learning Engineer I, Economist (post-PhD industry experience)
A PhD in Economics or a closely related field with a focus on data-intense problems
Intern experience in related roles
Experience with large language models and generative AI, both on the algorithm side as well as a day-to-day tool
Experience with uplift modeling, contextual bandits, and/or heterogeneous treatment effect estimation
Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants
CA, NY, CT, NJ
OR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI
All other states
Graduate Degree (Masters or PhD) in Economics or a closely related field
A blend of economic theory, applied econometrics, and business skills that let you jump into a fast-paced environment and contribute from day one
Experience applying causal inference methodologies to both observational and experimental datasets
An understanding of machine learning algorithms and techniques
Strong programming skills (Python) and fluency in data manipulation (SQL, Pandas) and machine learning tools (e.g., scikit-learn, XGBoost)
Excellent communication skills (both verbal and written)
Self-motivation and a strong sense of ownership
1-3 years of industry experience in a similar position
Experience putting machine learning models into production environments
Experience with cloud computing and related ML infrastructure