Senior Machine Learning Engineer, Portfolio ML

Key Skills

Deep Learning, Effective communication skills, Kubeflow, NumPy, Pandas, Python Programming, Ray.io, Scikit-learn, SPARK Programming, SQL, XGBoost

Job Description

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 Portfolio ML team is looking for an exceptional machine learning engineer to build the next generation of credit opportunity management models. Sitting at the intersection of credit policy and consumer product, this role will work within a highly cross-functional and diverse set of work-streams that contribute directly to profitability. From choosing which users to engage for repeat, finding the optimal value propositions to present them, and owning unit economics libraries, the Portfolio ML team’s focus spans the entire customer lifecycle including re-engagement. The team is relatively new and has a number of greenfield initiatives in its mandate, an exceptional group of ICs, and strong Product leaders in partnership.

What You'll Do

• Use Affirm’s proprietary and other third party data to develop machine learning models that manage and optimize the flow of loan opportunities across Affirm-owned and -operated properties
• Partner with platform and product engineering teams to build model training, decisioning, and monitoring systems
• Research ground breaking solutions and develop prototypes that drive the future of portfolio decisioning at Affirm
• Implement and scale data pipelines, new features, and algorithms that are essential to our production models
• Collaborate with the engineering, credit, and product teams to define requirements for new products

What We Look For

• Proficiency in machine learning with experience in areas such as Generalized Linear Models, Gradient Boosting, Deep Learning, and Probabilistic Calibration. Domain knowledge in credit risk, portfolio management, learning to rank, and personalization is a plus
• Strong engineering skills in Python and data manipulation skills like SQL
• Experience using distributed systems like Spark or Ray is a plus
• Experience using open source projects and software such as scikit-learn, pandas, NumPy, XGBoost, Kubeflow
• 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 - CAN 30

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

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.