Job intelligence
Analytics Engineer II, Full Stack (Revenue Analytics)
Affirm
Before relying on the listing: Confirm Application closing time with the employer or source. See verification questions
Executive opportunity brief
The decision in one screen
A compact evidence-first read of compensation, flexibility, mobility and what still needs verification. No universal quality score is used.
Fast read
Opportunity DNA
This opportunity needs a closer read before drawing a strong conclusion, especially around the salary benchmark is still shallow.
The range is usable, but the comparable sample is still too shallow for a strong relative-pay call.
The work arrangement can be assessed, although it is not among the most flexible patterns detected.
Some access and qualification signals are clear, but the overall entry path is neither unusually open nor unusually restrictive.
Sponsorship and relocation support are not clear from the current listing.
Part of the application route can be assessed, but the full external process may contain additional steps.
At least one recent enabled source can still renew this vacancy.
This fingerprint summarizes what is clear, constrained or still unanswered in the current listing. It is a reading aid, not an overall job score.
Decision evidence check
4 of 5 core facts stated
This checks whether the listing states the facts that commonly change an employment decision. It measures disclosure completeness, not whether the opportunity is good or bad.
Facts already stated
- Compensation
- Work arrangement
- Advertised location
- Employment type
What to verify next
- Application closing time: Is there a firm application deadline, a rolling review window or no stated closing date?
Advertised location is not proof of work authorization, sponsorship, or legal eligibility. Unknown information is not a negative score; verify those questions separately.
Decision levers
What could make or break the fit?
Reasons to look closer
Nothing stands out strongly enough yet to call a clear advantage. The role may still be attractive for reasons the listing does not spell out.
Trade-offs to weigh
- The salary benchmark is still shallow: Pay is disclosed, but the current comparison pool is too small for a strong relative-pay conclusion.
Questions worth asking before you invest more time
- Confirm which countries employees may work from and whether payroll-country, timezone or office-attendance restrictions apply.
- Confirm whether a degree is actually required, preferred, or replaceable with equivalent experience.
- Ask whether visa sponsorship is available before investing significant time in the application.
These questions come from details the listing leaves open. An unanswered point is not treated as a disadvantage.
Opportunity neighborhood
Keep your options open
These live roles sit close enough to this opportunity to make useful comparison points. Look across several employers before deciding what pay, flexibility or access trade-offs you are willing to accept.
Embedded AI Engineer, On-Device Models
Deepgram · USA
Why it is nearby: Same seniority band · Similar work arrangement · Same employment type
Different angle: Different country
Senior AI Engineer (GTM)
Paddle · UK
Why it is nearby: Same seniority band · Same employment type · Recently posted
Different angle: Different country · Different work arrangement
Senior Data Scientist - Credit Risk Modelling
iwoca · London
Why it is nearby: Same seniority band · Same employment type · Recently posted
Different angle: Different work arrangement
Senior Machine Learning Engineer - Messaging Platform
Spotify · London
Why it is nearby: Same seniority band · Same employment type · Recently posted
Different angle: Different work arrangement
This neighborhood is drawn from current inventory in the same broad occupation. Similarity is based on explicit listing facts; missing details do not count against a job.
Role market context
How much current choice is visible around this kind of work?
This compares the vacancy with current High Paid Job inventory in the broad Data & AI roles family. It describes visible choice and disclosure, not future demand or career quality.
200 most recent current roles sampled for the disclosure measures below.
Distinct employers in the bounded current sample, not an estimate of all employers hiring in the market.
Current sampled roles stating at least four of the five Core Decision Facts.
Requires a numeric amount, explicit ISO currency and supported pay period.
Listings with explicit enough remote, hybrid or on-site evidence to classify.
Missing deadline evidence remains unknown and is not interpreted as an open-ended application window.
Currencies with explicit pay evidence in the sample: USD (42) · EUR (6) · GBP (3) · CHF (1). Raw amounts across different currencies are not compared.
This describes current visible High Paid Job inventory in the same broad occupation family. Percentages use a bounded recent sample and are not a forecast, a complete labor-market census or an employer-quality measure.
Constraint opportunity lab
What changes the size of the current opportunity pool?
Each line applies one stricter evidence-based constraint to the same bounded current role-family sample. It helps you see the trade-off in visible choice without deciding which trade-off is right for you.
Counts only affirmative or possible sponsorship evidence, or relocation explicitly offered. Unknown is not treated as no.
Uses only roles where a country is known. Roles without country evidence are excluded from this denominator.
A much stricter subset: only listings with explicit worldwide-remote evidence remain.
Counts roles explicitly classified as worldwide remote, region-restricted remote or remote with restrictions still unclear.
Shows the subset with enough stated evidence for a more informed first comparison.
Requires amount, explicit ISO currency and a supported pay period. Missing pay evidence remains unknown.
Includes roles whose seniority is genuinely unspecified rather than assuming they belong to another level.
Uses only roles with a stated employment type.
These are counterfactual filters over a bounded sample of current HPJ inventory in the same broad occupation family. They show how visible choice changes when one evidence-based constraint is applied; they do not tell you which constraint you should choose or predict hiring outcomes. The calculation uses the 200 most recent current roles from 1258 visible roles in this broad family.
Salary transparency context
Is pay disclosure typical for this kind of role?
This listing states usable structured compensation. About 26% of the bounded current role sample does the same.
Compensation counts only when amount, ISO currency and supported pay period are all known.
Pay disclosure is limited in the current role sample.
This employer’s current visible listings disclose pay materially more often than the current same-role sample.
This compares salary-disclosure behavior in current visible listings. It does not compare raw salary amounts across currencies, infer undisclosed pay as zero, or rate employer quality.
Private offer & negotiation lab
Turn an offer into evidence, not guesswork
Enter an annual base offer and, if you want, your own target. HPJ compares only within one explicit currency and never chooses a target for you.
Negotiation evidence available: advertised pay range, strong decision evidence.
Enter an annual base offer to compare it with explicit same-currency evidence. HPJ will not suggest a target for you.
Review the full package · 10 terms
Mark what is confirmed, what needs clarification and what you want to prioritize. These choices and notes stay in this browser.
Usable advertised compensation is available.
Variable compensation is mentioned; verify amount, formula, target and eligibility.
Equity or long-term incentive language is mentioned; verify grant type, vesting and valuation basis.
Retirement or pension benefits are mentioned; verify employer contribution and vesting.
Health-benefit language is mentioned; verify coverage, dependants and employee cost.
Paid-leave language is mentioned; verify the exact entitlement and carry-over rules.
A work-arrangement signal is available; verify schedule details before relying on it.
Relocation support not established
Sponsorship not established
A review cycle is mentioned; verify timing and whether compensation can change at that review.
Questions worth taking into the offer conversation
- Is there a bonus, commission or other variable-pay component, and how is it calculated?
- What retirement or pension contribution does the employer provide?
- What health coverage is included and what costs remain with the employee?
- If relocation is relevant, what expenses, timing and repayment conditions are covered?
- What exact sponsorship or work-authorization conditions apply to this role?
- When is the first performance and compensation review after joining?
- Is there a firm application deadline, a rolling review window or no stated closing date?
Occupation intelligence
What broader career references connect to this role?
HPJ uses broad comparison families for current-market analysis. External taxonomy results are reference candidates for that broad family, not a declaration that this vacancy has been authoritatively classified into a specific occupation.
European occupation references
This service uses the ESCO classification of the European Commission.
U.S. occupation references
- Data Scientists 15-2051.00
- Computer and Information Research Scientists 15-1221.00
- Social Science Research Assistants 19-4061.00
- Atmospheric and Space Scientists 19-2021.00
- Bioinformatics Scientists 19-1029.01
This site incorporates information from O*NET Web Services by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). O*NET® is a trademark of USDOL/ETA.
Career reference research
Skills worth investigating
Official occupational context, paired with exact phrases visible in this vacancy. It is not a skills test or an applicant-fit score.
ESCO · European occupation
data scientist
Usually essential in this ESCO occupation
- statistics
- think abstractly
- apply research ethics and scientific integrity principles in research activities
- integrate gender dimension in research
- promote the participation of citizens in scientific and research activities
- communicate with a non-scientific audience
- implement data quality processes
Context-dependent ESCO skills
- Hadoop
- unstructured data
- apply blended learning
- teach in academic or vocational contexts
- digital curation
O*NET · U.S. occupation
Data Scientists
O*NET occupation skills
- Mathematics
- Critical Thinking
- Reading Comprehension
- Complex Problem Solving
- Programming
- Active Learning
- Speaking
- Active Listening
Build my private skill preparation brief Your evidence · Practice · Interview questions
Plan how you might demonstrate or investigate occupational skills. These are broad-family reference examples, not confirmed vacancy requirements. Nothing you enter is sent to High Paid Job.
Private to this browser. Up to 20 reference skills; not a qualification assessment or hiring prediction.
Useful next question: Which of these occupational reference skills does the hiring manager actually expect for this specific role, and what evidence would demonstrate them?
These skills belong to one reference occupation selected for HPJ’s broad career family, not a verified classification of this vacancy. Text overlap only means a phrase appears in the available listing text; it does not establish an employer requirement, your proficiency, or a qualification gap. A missing mention is unknown, not a deficit.
Adjacent current roles to investigate
Sr Staff Site Reliability Engineer
Cribl · Australia
same seniority band · same employment type · similar work-arrangement evidenceProduct Enablement Manager
Zone & Co · USA
same employment type · similar work-arrangement evidenceSenior Quality/Test Engineer POS & Retail Systems-Banking
Stockholm · STOCKHOLM, Stockholms län, Sverige
same seniority band · same employment typeAdjacent-family roles are exploration prompts from current HPJ inventory. They are not inferred qualification matches and they do not imply a promotion path.
Career move map
What sits one step away?
This listing is currently read as Senior / lead. Nearby roles one visible seniority step away can help you judge whether to widen the search, stretch upward or compare the responsibilities more carefully.
Broader-entry direction
Data Engineer & PowerBI Developer
LUZA Group · Remote — Worldwide
Similar work arrangement · Same employment type · Recently postedData Analyst
Naples Jet Center · Remote — Worldwide
Similar work arrangement · Same employment type · Recently postedStretch direction
Staff Analytics Engineer
Monzo · UK
Similar work arrangement · Same employment type · Recently postedStaff Data Scientist
hims & hers · USA
Similar work arrangement · Same employment type · Recently postedThese are live roles one visible seniority step away in the same broad occupation family. They can reveal nearby options, but they are not a guaranteed promotion path and do not account for your personal experience.
Skill bridge
What does this role connect to?
Databricks is one of the signals this listing shares with skills appearing often across current Data & AI roles opportunities.
Skills named in this listing
Shared with the current career sample
- Databricks Seen in 22 sampled listings
- Python Seen in 85 sampled listings
- Snowflake Seen in 21 sampled listings
- SQL Seen in 77 sampled listings
Combinations also appearing together
- Python + SQL appeared together in 64 sampled listings
Additional signals in this listing: Salesforce
Application edge
- If these skills match your background, prepare one concrete example that shows how you used Databricks, Python, and Salesforce rather than relying on a keyword-only claim.
- The listing states about 3 years of required experience. Check that the dates and scope in your application make that experience easy to verify.
If the named skills are genuinely transferable in your own experience, the occupation map also points to adjacent current families worth researching: Software engineering roles and Product roles. This is exploration context, not a qualification match.
Skill signals come from explicit text mentions. A mention is not automatically a requirement, and absence from the current top-skill list does not make a skill rare or unimportant. The current career comparison draws on 120 sampled listings; 117 contain a recognized skill signal.
Application Decision Lab
Turn the listing into a preparation plan
Separate what the listing actually states from what you still need to prepare or verify. Your selections and short notes stay in this browser and are never submitted to High Paid Job.
At least about 3 years of experience required
The available wording contains an explicit minimum/required years-of-experience signal. Preferred years are tracked separately and never promoted into the required minimum.
Databricks
This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.
Python
This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.
Salesforce
This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.
Snowflake
This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.
SQL
This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.
Tableau
This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.
Questions worth resolving before you rely on the opportunity
- Application closing time: Is there a firm application deadline, a rolling review window or no stated closing date?
- Work authorization / sponsorship: If sponsorship or work authorization matters to you, what exact immigration or employer-sponsorship conditions apply to this role?
- Application process: What interview, assessment, portfolio, reference or screening stages are part of the hiring process?
Decision analysis
What the listing really tells you
The headline alone does not tell the whole story for Analytics Engineer II, Full Stack (Revenue Analytics) at Affirm. The clearest decision context comes from pay is visible, but the benchmark is still thin, work-location flexibility has usable detail, and the entry path is becoming clearer.
Pay is visible, but the benchmark is still thin
A usable PLN salary is available, but there are not enough comparable current observations for a strong percentile statement yet.
Work-location flexibility has usable detail
Location flexibility can be assessed here: Remote with some uncertainty or restrictions, with a Remote Freedom reading of 68/100.
The entry path is becoming clearer
At least about 3 years of experience required · 1 additional stated barrier. Only requirements actually stated in the listing are counted; anything left unsaid remains unresolved.
The visible application effort can be estimated
Provider-mediated application path. The external application may contain additional steps that are not visible from the listing itself.
The listing can be traced to a current source
1 recent enabled source can currently renew this vacancy across 1 source classes. That improves traceability, although it does not verify the employer itself.
How this analysis is assembled
Built from the pay, location, qualification, mobility, application and source details available for this vacancy. Anything the listing leaves unresolved stays unresolved.
Analysis evidence coverage
How much analysis can the current evidence support?
Only 0 comparable salary observations are available. At least 10 are needed before showing a High Pay Score.
Measures observable location flexibility and explicit restrictions; it does not determine whether remote work is personally desirable.
The salary is source-provided and normalizable, but the advertised range is broad enough to reduce comparison precision.
The listing was posted about 4 days ago.
At least one enabled source recently observed the vacancy. The source chain is traceable, but this is not independent employer verification.
There is no universal opportunity score because pay, flexibility and access matter differently to different people. Compare Jobs lets you weight the evidence around your own priorities.
Decision checklist
What is supported, uncertain or worth checking?
This checklist separates supported strengths, visible cautions and missing evidence. It is not an overall recommendation or guarantee that the job is suitable for you.
Supported strengths
No standout strength is supported strongly enough to list here. That is not a negative rating.
Visible cautions
- At least about 3 years of experience required
Still unknown
- There is not enough comparable salary evidence to establish this job’s current pay position.
- Visa sponsorship is not established by the available listing data.
Pay vs. barriers
Opportunity Efficiency not assessed
The current pay position is not reliable enough to weigh compensation against the stated barriers.
1 explicit required barrier is visible in the available wording.
The listing states at least about 3 years of required experience.
- Current comparable pay position is unavailable.
- Education requirement is not established.
This section weighs pay context against clearly stated barriers without collapsing unlike requirements into one universal score. Degree, experience, licensing, clearance and location limits remain separate, and missing qualification details stay unknown.
Beyond the headline
Not enough evidence for a hidden-value finding
Potential hidden value appears only when several distinct non-pay advantages are actually supported. Missing requirements or benefits are never counted as positives.
Still check: At least about 3 years of experience required · The current application path is provider-mediated rather than directly classified as an employer-authorized or official route.
Hidden Value is an experimental evidence summary, not an investment-style score or guarantee of employability. It only uses explicit current listing evidence and does not infer that an unmentioned qualification is unnecessary.
Compensation intelligence
How competitive is this pay?
Only 0 comparable salary observations are available. At least 10 are needed before showing a High Pay Score.
Why this analysis?
- Only 0 comparable salary observations are available. At least 10 are needed before showing a High Pay Score.
- Salary confidence: Medium. The salary is source-provided and normalizable, but the advertised range is broad enough to reduce comparison precision.
- Range quality: Broad but usable range.
Employer compensation communication
Pay transparency at Affirm
Good current pay transparency
This score uses the employer’s current visible listings and combines how often pay is disclosed with how useful those ranges are. Bonus, equity and benefit mentions are shown separately and do not raise the score.
This pattern comes from the employer’s current visible vacancies. It describes hiring and pay transparency in those listings, not employee satisfaction or a permanent judgement of the employer.
Current employer intelligence
Affirm — current opportunity snapshot
Employer Evidence Profile
How often this employer’s current visible sampled vacancies state decision-critical information. These percentages describe evidence coverage, not employer quality.
Current sampled listings with advertised compensation evidence.
Current sampled listings whose work arrangement is clearer than unknown.
Current sampled listings with a supported country signal.
Current sampled listings with an explicit closing time.
Current sampled listings with a usable posting date.
Current sampled listings that explicitly indicate confirmed, possible or unavailable sponsorship evidence.
Current sampled listings with an explicit relocation signal.
Low coverage means the current visible listings state the information less often. It does not prove that the employer lacks the policy, benefit or support.
Common current occupation families: Software engineering (10) · Data & AI (4) · Product (2)
Visible seniority mix: Mid-career (1) · Senior / lead (7) · Leadership (5)
Current employment-type mix: Full time (15) · Contract (1)
Most visible hiring countries in this sample: United Kingdom (3) · United States (2) · Poland (2) · Australia (1)
Other current roles from this employer
Executive Assistant III
UK
Leadership · Region-restricted remoteAnalytics Lead, Deposit Fraud Risk
USA
Leadership · Region-restricted remoteSenior Software Engineer, Backend (International)
Senior / lead · On-site / hybridSoftware Engineer II, Backend (Payments)
Seniority not clearly specified · On-site / hybridThese are other current vacancies visible from the same employer, not endorsements or evidence of future hiring plans.
Current disclosed salary medians by currency
- GBP 144,000 median · 13 disclosed salaries
Questions worth asking this employer
- If work authorization matters to you, what sponsorship policy applies to this specific role and location?
- If a move is required, is relocation assistance available for this position?
- What is the expected application and interview timeline if the listing does not state a closing date?
These questions are prompted by missing or thin evidence in the employer’s current visible vacancies. Missing evidence is not treated as a negative judgement.
This employer snapshot uses the employer’s current visible listings. Remote and sponsorship rates use only vacancies with explicit evidence, while missing information stays unknown. Salary medians are shown separately by currency and need at least five disclosed salaries. Zero confirmed sponsorship means none was explicitly found in this sample, not that sponsorship is unavailable.
This snapshot describes the employer’s current visible vacancies—things such as pay disclosure and work arrangement. It is not an employee-satisfaction or hiring-quality rating, and different currencies stay separate.
Work-location intelligence
Remote Freedom
Remote with some uncertainty or restrictions
Why this score?
- The role is remote, but the exact applicant-location restrictions are not clear.
Remote Freedom measures observable location flexibility only. Unknown work-location information remains unscored. Timezone wording is penalized only when it appears restrictive; general collaboration across time zones is not treated as a restriction. A score does not guarantee legal work eligibility, payroll availability or visa sponsorship.
International applicant intelligence
Visa & relocation signals
Sponsorship status is shown only when the listing provides clear enough wording. Employer history or headquarters location is not used to guess an answer.
The available listing details do not contain a clear enough sponsorship statement.
The available listing details do not contain a clear enough relocation statement.
Tradeoff check
What’s the catch?
No obvious trade-off appears in the available job details. That does not mean the role has no drawbacks, so the original listing and employment terms are still worth reading carefully.
Application-path intelligence
What can we see about the application process?
Provider-mediated application path
The current application path comes through a publisher or aggregator. The destination may still lead to an employer-authorized hiring system, but that is not clear enough to assume.
Current destination: jobicy.com · HTTPS
No additional required application step is clear in the available listing text. This does not mean the external application is one-click or friction-free.
Application effort is estimated from visible listing and source details. Optional steps are kept separate from mandatory ones, and the external form may contain additional requirements that are not visible here.
Application safety context
Application safety check
Basic application-safety context available
The current application destination has a basic transport-safety signal such as HTTPS. This does not verify the employer, vacancy, recruiter or application process.
Evidence checked: Source provenance · Application destination · Listing wording
Observable transport-safety signals
- The available application destination uses HTTPS.
Before you share money or sensitive information
- Confirm the vacancy on the employer’s official careers site when practical, especially if a recruiter contacts you outside the listed application path.
- Check that recruiter email domains and application destinations are consistent with the employer or an identifiable recruiting provider.
- Do not pay application, processing, training or equipment fees merely to be considered for a job.
- Do not send cryptocurrency, gift cards, online-banking credentials or PINs as part of an application.
- Treat unusually fast offers or interviews conducted only through informal messaging channels as reasons to verify the employer independently.
This is a limited safety screen, not employer verification and not a fraud determination. Never send money, cryptocurrency, passwords or sensitive banking credentials merely because a listing appears on a job platform.
Original listing details
The section below comes from the listing source. The decision sections above use the job’s structured pay, location, qualification, mobility and application details to give you additional context.
At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most.
We’re looking for a curious, driven professional to join our Revenue Analytics team. This builds and owns the data products, reporting infrastructure, semantic foundations, and analytical systems that power Affirm’s Revenue organization.
As a Senior Analyst, Revenue Analytics, you’ll build scalable data products that power day-to-day decision-making - owning end-to-end work across data modeling, metric definitions, dashboards, automation, and enablement.
You’ll also help strengthen our semantic layer and data governance, laying the foundation for reliable AI. The ideal candidate combines strong technical and analytical skills with the ability to turn ambiguous business questions into durable, well-tested data infrastructure.
What you'll do
-
Develop dbt data models, dashboards, metrics, and automation processes for the revenue field team and revenue analysts
-
Build and maintain critical reporting data models that power external merchant reporting
-
Build the semantic, metadata, and context layers that allow AI systems to accurately understand Revenue data, metrics, and business definitions
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Partner with Business Systems, engineering, and business stakeholders to translate requirements into durable, well-tested data products
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Contribute to the team’s best practices in version control, code review, documentation, and release hygiene (GitHub-based workflows)
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Develop processes, governance, and foundations to scale the impact of analytics within Revenue.
What we look for
-
3+ years of work experience in an analytics engineering or business intelligence role
-
Strong working knowledge of SQL, dbt, Python, data modeling, and data visualization
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Hands-on experience with BI tools (Sigma/Looker/Tableau), Databricks, and cloud data warehouses (Snowflake)
-
Understanding of the data foundations required for reliable AI, including semantic layers, metadata, evals, metric definitions, documentation, and data quality
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Demonstrated experience integrating AI tools into day-to-day analytics engineering workflows to improve development speed, quality, and scalability
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Familiarity with Salesforce and experience supporting commercial areas of the business
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Ability to identify user needs and translate them into robust, scalable data products
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Ability to start with an ambiguous problem, deconstruct it into tangible steps, and work toward an impactful solution
-
Ability to communicate findings and recommendations clearly to both technical and non-technical audiences.
Total rewards
We believe the people building honest financial products at Affirm should share in its success. That's why our total rewards are designed to support your health, growth, financial well-being, and future.
In service of our mission, we reward employees through a combination of base pay, equity (from parent company), and comprehensive benefits.
Base Pay Grade - K
226 000 zł - 346 000 zł
Base pay ranges and placement within those ranges are determined based on several factors, including role, experience, and job-related skills.
In addition to base pay, all employees in this role are eligible to receive equity from the parent company each year. This means as Affirm’s parent company grows, employees have the opportunity to share in that growth financially.
Equity Grade - 2 (awarded in US Dollars)
Affirm Holdings, Inc. Equity Grade example
Equity grade: 2
New hire equity: $16,000-$24,000
Annual Refresh: $5,000
Reward equity: $0-$75,000
Affirm also provides flexible spending wallets to all employees for technology and wellbeing related needs, which are reimbursable up to 1390 zł per month.
In addition to your compensation, our comprehensive benefits are designed to support you and the people who matter most. Benefits include:
- Competitive paid time off, paid public holidays, and additional paid Away Days to rest and recharge.
- Comprehensive private healthcare through Lux Med's Platinum package.
- A MultiSport card to support your health and well-being.
- Learning and development programs to help you grow professionally.
- Family healthcare support through Maven and parental leave support through Parentaly.
- Mental well-being support through Lyra, including up to 12 confidential counseling or coaching sessions each year for you and your household members.
- Financial well-being support through Northstar, with unlimited access to Certified Financial Advisors and planning tools at no cost to you.
- Employee Resource Groups (ERGs) that foster connection and inclusion.
- Eligibility for creative tax benefits, subject to applicable law, role, 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
Remote-first with flexibility built in
Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience.
Benefits designed for you
Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights:
- Health coverage at no cost: We cover 100% of premiums for employees and their dependents.
- Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you.
- Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to.
- Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount.
We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help.
For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law.
By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.
Listing provenance
Where did this job come from?
See where this vacancy came from and whether more than one current source can still support it. Source names help with traceability and attribution; they are not endorsements or guarantees.
At least one enabled source recently observed the vacancy. The source chain is traceable, but this is not independent employer verification.
- Continuity
- One recent renewable source
- Source-class independence
- One renewable source class
- Last source observation
- Observed in the current source window
This records when High Paid Job last observed the vacancy in source evidence. It confirms source presence, not that the employer edited the vacancy at that time.
- 1 enabled source recently observed this vacancy.
Source confidence is about traceability and continuity. It is separate from application safety and should not be read as an employer reputation rating.
The vacancy is supplied by an external job publisher. Source information helps show where the listing came from; it is not a guarantee about the employer or vacancy.
Listing source: Jobicy. Destination: jobicy.com. The application opens in a new tab so you can keep this report open.