Analytics Engineer Jobs at Affirm with Visa Sponsorship
Affirm hires Analytics Engineers to build and maintain the data infrastructure that powers credit and payments decisions. The company has a consistent track record of sponsoring work visas for this function, covering both initial sponsorship and long-term immigration pathways for qualified candidates.
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INTRODUCTION
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. Join the Affirm team as a Senior Staff Machine Learning Engineer and become a pivotal part of our innovative ML team. Our team is dedicated to Affirm's mission of revolutionizing financial services with transparency and inclusivity at its core. We are utilizing advanced machine learning techniques ensuring responsible and accessible financial products. In this role, you will help shape the future of machine learning at Affirm. You’ll partner with ML Platform, engineering, product, and risk leaders to design, implement, and scale advanced modeling approaches that drive critical decisions across the company. You will elevate our modeling capabilities, influence architectural direction, and ensure our systems can support increasingly sophisticated workloads. You will mentor senior engineers, bring clarity to complex, ambiguous problems, and contribute to a cohesive long-term ML strategy. If you are passionate about modern machine learning and excited to drive high-impact innovation across a growing organization, Affirm is the place for you.
ROLE AND RESPONSIBILITIES
You will define and drive multi-year, multi-team technical strategy for machine learning across Affirm, ensuring alignment with company-wide priorities and influencing the roadmaps of partner teams and platforms.
You will lead the design, implementation, and scaling of advanced ML systems, setting the architectural direction for complex, cross-functional initiatives and ensuring systems remain reliable, extensible, and prepared for increasingly sophisticated modeling workloads.
You will partner deeply with ML Platform, product, engineering, and risk leadership to shape long-term modeling capabilities, define new opportunities for ML impact, and guide infrastructure evolution required for next-generation ML methods.
You will provide broad technical leadership across the ML organization, mentoring senior engineers, elevating design and code quality, and spreading ML expertise through documentation, talks, and cross-org guidance.
You will drive clarity and alignment on ambiguous, high-stakes technical decisions, resolving cross-team tensions, balancing competing priorities, and exercising judgment optimized for the broader engineering organization.
You will champion operational and system excellence at the area level, owning the long-term health, availability, and evolution of critical ML systems, and ensuring robust testing, monitoring, and reliability practices across teams.
BASIC QUALIFICATIONS
You have 10+ years of experience researching, designing, deploying, and operating large-scale, real-time machine learning systems, with a proven record of driving technical innovation and delivering measurable business impact. Relevant PhD can count for up to 2 YOE.
You have experience leading end-to-end ML system design, from data architecture and feature pipelines to model training, evaluation, and production deployment. You use distributed frameworks such as Spark, Ray, or similar large-scale data processing systems.
You are proficient in Python and ML frameworks, including PyTorch and XGBoost. You are experienced with ML tooling for training orchestration, experimentation, and model monitoring, such as Kubeflow, MLflow, or equivalent internal platforms.
You have a strong understanding of representation learning and embedding-based modeling. You possess deep expertise in neural network-based sequence modeling, including architectures such as Transformers, recurrent, or attention-based models, and multi-task learning systems. You are comfortable designing and optimizing models that learn from sequential or temporal event data at scale.
You have deep hands-on experience with large-scale distributed ML infrastructure, including streaming or batch data ingestion, feature stores, feature engineering, training pipelines, model serving and inference infrastructure, monitoring, and automated retraining.
You provide strong technical leadership: defining long-term strategy, guiding research direction, and aligning work across teams. You are recognized as a trusted expert who can drive clarity and execution even in ambiguous problem spaces.
You demonstrate exceptional judgment, collaboration, and communication skills, enabling effective technical discussions with engineers, researchers, and executives. You mentor senior engineers, foster technical excellence, and contribute to a culture of continuous learning.
You have strong verbal and written communication skills that support effective collaboration across our global engineering organization.
This position requires equivalent practical experience or a Bachelor’s degree in a related field.
COMPENSATION
- Pay Grade - R
- Equity Grade - 15
Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.
Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.)
USA base pay range (CA, WA, NY, NJ, CT) per year: $260,000 - $310,000
USA base pay range (all other U.S. states) per year: $232,000 - $282,000
LOCATION
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.
BENEFITS
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.
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 Affirm's Global Candidate Privacy Notice and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.

INTRODUCTION
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. Join the Affirm team as a Senior Staff Machine Learning Engineer and become a pivotal part of our innovative ML team. Our team is dedicated to Affirm's mission of revolutionizing financial services with transparency and inclusivity at its core. We are utilizing advanced machine learning techniques ensuring responsible and accessible financial products. In this role, you will help shape the future of machine learning at Affirm. You’ll partner with ML Platform, engineering, product, and risk leaders to design, implement, and scale advanced modeling approaches that drive critical decisions across the company. You will elevate our modeling capabilities, influence architectural direction, and ensure our systems can support increasingly sophisticated workloads. You will mentor senior engineers, bring clarity to complex, ambiguous problems, and contribute to a cohesive long-term ML strategy. If you are passionate about modern machine learning and excited to drive high-impact innovation across a growing organization, Affirm is the place for you.
ROLE AND RESPONSIBILITIES
You will define and drive multi-year, multi-team technical strategy for machine learning across Affirm, ensuring alignment with company-wide priorities and influencing the roadmaps of partner teams and platforms.
You will lead the design, implementation, and scaling of advanced ML systems, setting the architectural direction for complex, cross-functional initiatives and ensuring systems remain reliable, extensible, and prepared for increasingly sophisticated modeling workloads.
You will partner deeply with ML Platform, product, engineering, and risk leadership to shape long-term modeling capabilities, define new opportunities for ML impact, and guide infrastructure evolution required for next-generation ML methods.
You will provide broad technical leadership across the ML organization, mentoring senior engineers, elevating design and code quality, and spreading ML expertise through documentation, talks, and cross-org guidance.
You will drive clarity and alignment on ambiguous, high-stakes technical decisions, resolving cross-team tensions, balancing competing priorities, and exercising judgment optimized for the broader engineering organization.
You will champion operational and system excellence at the area level, owning the long-term health, availability, and evolution of critical ML systems, and ensuring robust testing, monitoring, and reliability practices across teams.
BASIC QUALIFICATIONS
You have 10+ years of experience researching, designing, deploying, and operating large-scale, real-time machine learning systems, with a proven record of driving technical innovation and delivering measurable business impact. Relevant PhD can count for up to 2 YOE.
You have experience leading end-to-end ML system design, from data architecture and feature pipelines to model training, evaluation, and production deployment. You use distributed frameworks such as Spark, Ray, or similar large-scale data processing systems.
You are proficient in Python and ML frameworks, including PyTorch and XGBoost. You are experienced with ML tooling for training orchestration, experimentation, and model monitoring, such as Kubeflow, MLflow, or equivalent internal platforms.
You have a strong understanding of representation learning and embedding-based modeling. You possess deep expertise in neural network-based sequence modeling, including architectures such as Transformers, recurrent, or attention-based models, and multi-task learning systems. You are comfortable designing and optimizing models that learn from sequential or temporal event data at scale.
You have deep hands-on experience with large-scale distributed ML infrastructure, including streaming or batch data ingestion, feature stores, feature engineering, training pipelines, model serving and inference infrastructure, monitoring, and automated retraining.
You provide strong technical leadership: defining long-term strategy, guiding research direction, and aligning work across teams. You are recognized as a trusted expert who can drive clarity and execution even in ambiguous problem spaces.
You demonstrate exceptional judgment, collaboration, and communication skills, enabling effective technical discussions with engineers, researchers, and executives. You mentor senior engineers, foster technical excellence, and contribute to a culture of continuous learning.
You have strong verbal and written communication skills that support effective collaboration across our global engineering organization.
This position requires equivalent practical experience or a Bachelor’s degree in a related field.
COMPENSATION
- Pay Grade - R
- Equity Grade - 15
Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.
Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.)
USA base pay range (CA, WA, NY, NJ, CT) per year: $260,000 - $310,000
USA base pay range (all other U.S. states) per year: $232,000 - $282,000
LOCATION
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.
BENEFITS
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.
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 Affirm's Global Candidate Privacy Notice and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.
See all 64+ Analytics Engineer at Affirm jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Analytics Engineer at Affirm roles.
Get Access To All JobsTips for Finding Analytics Engineer Jobs at Affirm Jobs
Frame your SQL and dbt skills precisely
Affirm's Analytics Engineering roles consistently require proficiency in dbt, SQL, and data modeling for financial products. Tailor your resume to reflect experience with large-scale transaction datasets or credit risk pipelines so your application maps cleanly to the role.
Target roles tied to core lending products
Affirm structures analytics teams around product lines like buy-now-pay-later and merchant networks. Roles attached to these core revenue areas tend to move faster through headcount approval, which matters when your OPT or grace period has a hard deadline.
Clarify sponsorship scope before your offer call
Affirm sponsors both H-1B and Green Card pathways, but the PERM labor certification timeline for EB-2 and EB-3 runs independently of your H-1B status. Ask the recruiter directly which immigration pathways the team has initiated for prior Analytics Engineering hires.
Use Migrate Mate to filter Analytics Engineer openings
Affirm posts across multiple job boards, making it hard to isolate sponsorship-confirmed roles. Use Migrate Mate to filter Analytics Engineer positions at Affirm by the visa types relevant to your situation so you're only applying where your status fits.
Prepare your credential documentation before interviews
For H-1B specialty occupation eligibility, your degree must align with the Analytics Engineer role's core requirements. If your undergraduate degree is in a tangentially related field, gather transcripts and any professional certifications now so there are no delays if Affirm initiates an H-1B petition.
Understand how F-1 OPT bridges to H-1B at fintech employers
Affirm participates in E-Verify, which is required for STEM OPT extensions. If you're on F-1 OPT, confirm your degree field qualifies for the 24-month STEM extension early. That extension window is often what keeps the H-1B lottery timeline workable.
Analytics Engineer at Affirm jobs are hiring across the US. Find yours.
Find Analytics Engineer at Affirm JobsFrequently Asked Questions
Does Affirm sponsor H-1B visas for Analytics Engineers?
Yes, Affirm sponsors H-1B visas for Analytics Engineer roles. The company has an established immigration program that handles both initial H-1B filings and extensions. Because H-1B selection is subject to the annual lottery, Affirm typically coordinates with outside immigration counsel to file petitions in the April registration window for roles starting October 1.
Which visa types does Affirm commonly sponsor for Analytics Engineer roles?
Affirm sponsors H-1B, TN, and F-1 OPT and CPT for Analytics Engineers, and also supports EB-2 and EB-3 Green Card sponsorship for longer-term hires. TN is available to Canadian and Mexican nationals whose role qualifies under USMCA occupational categories. The right visa depends on your nationality, degree, and current status.
What qualifications does Affirm expect for Analytics Engineer roles?
Affirm's Analytics Engineer postings typically require a bachelor's degree or higher in computer science, statistics, mathematics, or a closely related quantitative field. Practical experience with dbt, SQL, and data pipeline tooling in a production environment is standard. Exposure to financial services data, such as transaction modeling or credit risk metrics, is a meaningful differentiator in the applicant pool.
How do I apply for Analytics Engineer jobs at Affirm?
You can apply directly through Affirm's careers page or browse confirmed sponsorship-eligible openings on Migrate Mate, which filters Affirm's Analytics Engineer roles by visa type so you can match your status before applying. Either way, tailor your application to reflect specific dbt or data modeling experience relevant to financial or payments infrastructure.
How do I plan my timeline when applying for an Analytics Engineer role at Affirm on a visa?
The most important variable is where you are in your current status. If you're on F-1 OPT, the STEM extension gives you up to 24 months of additional work authorization, but Affirm must be enrolled in E-Verify for that to apply. If H-1B sponsorship is the goal, the annual lottery cap means you'll need an offer confirmed well before the March registration window.
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