Staff Machine Learning Engineer (Underwriting)
Remote US
Affirm
With Affirm, you can pay over time at your favorite brands. No late fees or compounding interest—just a more responsible way to say yes to the things you love.Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest. Affirm, Inc. proudly includes Affirm, PayBright, and Returnly.
Affirm’s Machine Learning team solves problems critical to our business model - personalizing shopping experiences, detecting fraud, optimizing interest rates, and assessing creditworthiness in real time. Our innovative products necessitate the creation of novel machine learning solutions to drive both existing and new products.
What you'll do
- Use Affirm’s data to develop machine learning models that predict cash flows, financing programs, and optimize pricing for merchants.
- Build financial forecasting applications for Affirm’s two-sided marketplace
- Research ground breaking solutions and develop prototypes that drive the future of decisioning at Affirm
- Implement and scale data pipelines, new features, and algorithms that are essential to our production models
- Collaborate with the engineering, quantitative markets, merchant pricing, and product teams to define requirements for new products
- Evaluate new data sources to use in a cost-effective way in our models to add value
What we look for
- B.S. with 7+ years of industry experience, M.S. with 5+ years, or PhD with 4+ years
- Proficiency in machine learning with experience in areas such as gradient boosting, deep learning, recommendation systems, computational advertising, reinforcement learning, financial forecasting, time series analysis, anomaly detection, monte-carlo simulations, and Markov decision processes
- Strong programming skills in Python. Experience using frameworks for machine learning and data science like scikit-learn, pandas, numpy, XGBoost, TensorFlow, mllib
- Experience with the AWS technical stack and data infrastructure such as MySQL, Spark, Kubernetes, Docker, and Airflow
- Excellent written and oral communication skills and the capability to drive cross-functional requirements with product and engineering teams
- The ability to present technical concepts and results in an audience-appropriate way
- Persistence, patience and a great sense of responsibility – we build the decisioning that drives Affirm’s business!
Location - Remote U.S.
The majority of our roles can be located anywhere in the U.S. (exclusive of the U.S. Territories) and Canada (with the exception of Quebec).
#LI-Remote Affirm is proud to be a remote-first company! Employees in remote roles have the option of working remotely or from an Affirm office in their country of hire, and may occasionally travel to an Affirm office or elsewhere for required meetings or team-building events. Our offices in Chicago, New York, Pittsburgh, Salt Lake City, San Francisco and Toronto will remain operational and accessible for anyone to use on a voluntary basis, subject to local COVID-19 guidelines. If you got this far, we hope you're feeling excited about this role. Even if you don't feel you meet every single requirement, we still encourage you to apply. We're eager to meet people who believe in Affirm's mission and can contribute to our team in a variety of ways—not just candidates who check all the boxes. Inclusivity:At Affirm, People Come First is one of our core values, and that’s why diversity and inclusion are vital to our priorities as an equal opportunity employer. You can read about our D&I program here and our progress thus far in our 2020 DEI Report.
We also believe It’s On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.
By clicking "Submit Application," you acknowledge that you have read the Affirm Employment Privacy Policy, or the Affirm Employment Privacy Notice (EU) for applicants applying from the European Union, and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of my personal information as described therein.
Tags: Airflow AWS Data pipelines Deep Learning Docker Engineering Kubernetes Machine Learning ML models MySQL NumPy Pandas PhD Pipelines Python Research Scikit-learn Spark TensorFlow XGBoost
Perks/benefits: Team events
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