Staff Software Engineer (Machine Learning)

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 proudly includes Returnly.  The Merchant Insights Engineering team’s mission is to enable merchant partners to optimize Affirm value exchange to best support their unique business goals. This team works in close partnership with our product managers to build systems that bring unique value to our merchant partners. In particular, we focus on systems, models, and tools that help merchants intuitively understand how we support their business goals and the marginal value of partnering with Affirm. We strongly believe in aligning incentives between Affirm and our merchant partners such that we both win together. We are looking for highly motivated senior engineers to help build this team in Poland. Come join us! What You'll Do Design, develop, and deploy solutions that will help to bring value to the merchants’ business Build tools for partnering merchants to: 1) optimize their pricing programs, 2) analytics to help them understand the value of partnership with Affirm,  Partner with Analyst, Data Science, and Product engineering teams to build production machine learning models; your models will decide on the pricing strategies for merchant to help them achieve their business goals Develop our understanding of new data sources and how they may improve our existing processes Collaborate with other tech-leads, managers, and partners across Affirm's engineering, credit, marketing, and analytics teams to understand our performance modeling strategies, the business drivers underlying those strategies, and drive requirements for new products Serve as a trusted advisor on the application and implementation of machine learning across Affirm What We Look For B.S. with 8+ years of industry experience, M.S. with 7+ years, PhD with 6+ years, or equivalent experience Demonstrated experience designing real time systems and writing production-quality software Experience with the AWS technical stack and data infrastructure such as MySQL, Spark, Kubernetes, Docker, and Airflow 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 Excellent written and oral communication skills including the capability to drive requirements with product and engineering teams and present technical concepts and results in an audience-appropriate way Ability to work efficiently both solo and as part of a team; willingness to learn new things and mentor others Passion to change consumer banking for the better, while developing a deeper understanding of applied machine learning Compensation & Benefits We offer a competitive package, with some highlights listed below.  However, the given figures are not guaranteed compensation ranges; rather, they are unbinding, approximate indications of what the salary may be for your awareness. The actual salary may be less than the lower range or greater than the upper range, depending on skills and experience. No employee is guaranteed salary at the amount of the lower range. Targeted Gross Monthly Salary: 25,792 - 32,233 PLN  Type of employment: Contract of Employment Flexible Spending Wallets for tech, food and lifestyle Generous time off policies  Away Days - wellness days to take off work and recharge Learning & Development programs Parental leave Robust health benefits Employee Resource & Community Groups This role is eligible for creative tax benefits, subject to applicable law and company policy Location - Remote Poland The majority of our roles can be located anywhere in Poland. **This job description is not a contractual document, and is not intended to have binding force.** #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 hire. We have a simple and transparent remote-first grade-based compensation structure. Offer amounts within the range are based on a number of factors including but not limited to job-related skills, experience, and relevant education or training. Across the broader organization, certain roles are eligible for equity awards upon hire, promotion, tenure milestones and for performance. 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. 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.