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’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 proprietary and other third party data to develop machine learning models that predict the likelihood of fraud. These models will protect victims’ identities from being stolen, prevent Affirm from incurring financial loss, and increase the trust that consumers and partners have in the Affirm ecosystem
- Partner with the ML platform team to build fraud specific ML infrastructure
- Research ground breaking solutions and develop prototypes that drive the future of fraud decisioning at Affirm
- Implement and scale data pipelines, new features, and algorithms that are essential to our production models
- Collaborate with the engineering, fraud, and product teams to define requirements for new products
- Develop fraud models to maximize user conversion while minimizing fraud losses and data costs
What We Look For
- Bachelors in a technical field with 5+ years experience building and deploying ML models. Relevant PhD can count for up to 2 YOE
- Proficiency in machine learning with experience in areas such as gradient boosting, online learning, and deep learning. Domain knowledge in fraud risk is a plus
- Strong programming skills in Python
- Experience using large scale distributed systems like Spark and Ray
- Experience using machine learning frameworks such as scikit-learn, pandas, numpy, xgboost, and pytorch
- 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 strong sense of responsibility – we build the decision making that enables consumers and partners to place their trust in Affirm!
Pay Grade - CAN30
Employees new to Affirm or promoted into a new role, typically begin in the min to mid range.
CAN base pay range per year:
Min: $123,200
Mid: $154,000
Max: $184,800
Location - Remote CAN
#LI-Remote
Affirm is proud to be a remote-first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office. A limited number of roles remain office-based due to the nature of their job responsibilities.
We’re extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include:
- Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents
- Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses
- Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge
- ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount
We 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.
[For U.S. positions that could be performed in Los Angeles or San Francisco] Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, Affirm will consider for employment qualified applicants with arrest and conviction records.
By clicking "Submit Application," you acknowledge that you have read the Affirm Employment Privacy Policy for applicants within the United States, the EU Employee Notice Regarding Use of Personal Data (Poland) for applicants applying from Poland, the EU Employee Notice Regarding Use of Personal Data (Spain) for applicants applying from Spain, or the Affirm U.K. Limited Employee Notice Regarding Use of Personal Data for applicants applying from the United Kingdom, and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.
