Data Analytics Engineer Jobs at Affirm with Visa Sponsorship
Affirm hires Data Analytics Engineers to build the financial infrastructure behind its buy now, pay later platform, working across credit risk, payment data, and product analytics. Affirm has a consistent track record of sponsoring work visas for technical roles in this function, making it a realistic target for international 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+ Data Analytics Engineer at Affirm jobs
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Get Access To All JobsTips for Finding Data Analytics Engineer Jobs at Affirm Jobs
Align your portfolio to fintech data problems
Affirm evaluates candidates on experience with large-scale transactional data, credit modeling pipelines, and financial reporting systems. Before applying, update your portfolio to reflect work on payment data, fraud detection, or risk analytics rather than general analytics projects.
Verify your visa type matches the role level
Affirm sponsors multiple visa categories, including H-1B, TN, and F-1 OPT. Make sure your current status and the role's seniority level align before you apply, since a junior analyst role may not meet the specialty occupation threshold USCIS requires for H-1B approval.
Time your application around H-1B cap deadlines
If you need cap-subject H-1B sponsorship, Affirm must register you in the March lottery for an October 1 start. Target open roles at Affirm no later than January so there's runway to complete hiring, extend an offer, and file your registration before the USCIS window closes.
Use Migrate Mate to filter Affirm's open roles by visa type
Affirm posts Data Analytics Engineer roles across multiple teams and locations. Use Migrate Mate to filter specifically for positions at Affirm that align with your visa category, so you're not wasting applications on roles where sponsorship doesn't apply to your situation.
Prepare for DOL prevailing wage scrutiny in your offer negotiation
Affirm's LCA filings with the Department of Labor lock in a prevailing wage tied to your job title and work location. Understand the wage level for Data Analytics Engineer in your target city before negotiations, since your offered salary cannot fall below the certified LCA amount.
Document specialized skills that support an EB-2 or EB-3 petition
Affirm sponsors EB-2 and EB-3 Green Card pathways for engineering roles. Start gathering evidence of specialized skills, such as proprietary data architecture work or publications in financial analytics, early in your tenure so PERM labor certification documentation is ready when your employer initiates the process.
Data Analytics Engineer at Affirm jobs are hiring across the US. Find yours.
Find Data Analytics Engineer at Affirm JobsFrequently Asked Questions
Does Affirm sponsor H-1B visas for Data Analytics Engineers?
Yes, Affirm sponsors H-1B visas for Data Analytics Engineers. The role qualifies as a specialty occupation under USCIS standards given its requirement for a bachelor's degree or higher in a relevant technical field such as statistics, computer science, or data engineering. If you need cap-subject H-1B sponsorship, timing your application to allow for the March lottery registration window is essential.
Which visa types does Affirm commonly sponsor for Data Analytics Engineer roles?
Affirm sponsors H-1B, F-1 OPT, F-1 CPT, TN, and employment-based Green Card pathways including EB-2 and EB-3 for Data Analytics Engineer positions. F-1 OPT and CPT are commonly used by recent graduates entering the role, while TN applies to Canadian and Mexican nationals in qualifying technical occupations. H-1B is the primary long-term work visa for this role.
What qualifications and experience does Affirm expect for Data Analytics Engineer roles?
Affirm typically looks for candidates with a bachelor's or master's degree in data engineering, computer science, statistics, or a related quantitative field. Hands-on experience with SQL, Python, dbt, and cloud data warehouses such as Snowflake or BigQuery is expected. Background in financial services data, credit risk pipelines, or payment analytics is a meaningful differentiator given Affirm's core product focus.
How do I apply for Data Analytics Engineer jobs at Affirm?
You can browse and apply for Data Analytics Engineer openings at Affirm through Migrate Mate, which filters roles by visa sponsorship type so you can identify positions that match your immigration status. When applying, tailor your resume to reflect Affirm's fintech data stack and be prepared to discuss your work authorization situation early in the recruiter screen to avoid mismatches late in the process.
How do I navigate the Green Card process if I get a Data Analytics Engineer role at Affirm?
Affirm sponsors EB-2 and EB-3 Green Card pathways for engineering roles, typically initiated after you've established yourself in the position. The process begins with PERM labor certification filed with the DOL, which can take 12 to 18 months before an I-140 petition is filed with USCIS. Starting to document your specialized contributions early helps your employer build a stronger PERM application when the time comes.
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