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Payments Risk Analyst Jobs in Fairfield, NJ (NOW HIRING)

Indeed

Senior Insurance Analyst

Newark, NJ · On-site

Maintain and update risk management documentation (e.g., certificates of insurance, local policies ... Partner with Finance to ensure premium payments are timely, accurately recorded, and aligned with ...

SeatGeek

Senior Data Analyst, Risk Analytics

New York, NY · On-site +1

$108K - $157K/yr

Collaborate with Risk Ops agents, the manager, and cross-functional partners in Engineering, Payments, and CX to translate analysis into action What you have * 3+ years of experience in fraud ...

SeatGeek

Senior Data Analyst, Risk Analytics

New York, NY · On-site

$108K - $157K/yr

Collaborate with Risk Ops agents, the manager, and cross-functional partners in Engineering, Payments, and CX to translate analysis into action What you have * 3+ years of experience in fraud ...

American Express

Sr Mgr - Audit

Manhattan, NY · On-site

$103K - $174K/yr

... payment operating models, including associated operational, financial, and technology risks. * Experience with data analytic tools, data visualization, key risk indicators (KRIs), key performance ...

Inizio Partners

Product Manager

New York, NY · On-site

Payments, Risk, Compliance, Design, Operations etc. on key inputs and drive results * Support the ... Strong analytical skills with the demonstrated ability to research and make decisions based on the ...

Coast

Risk Manager

New York, NY · On-site

... payment extensions, adjusting grace periods, activating high-risk categories, or handling other judgment-based decisions that require thoughtful analysis. * You step in wherever needed to support ...

Coast

Risk Manager

New York, NY · On-site

... payment extensions, adjusting grace periods, activating high-risk categories, or handling other judgment-based decisions that require thoughtful analysis. * You step in wherever needed to support ...

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All JobsPayments Risk Analyst JobsPayments Risk Analyst Jobs in Fairfield, NJ

Payments Risk Analyst information

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$41

$67

How much do payments risk analyst jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for payments risk analyst in Fairfield, NJ is $41.28, according to ZipRecruiter salary data. Most workers in this role earn between $30.38 and $50.24 per hour, depending on experience, location, and employer.

What is a payments risk analyst?

Payments Risk Analysts are professionals responsible for identifying, assessing, and mitigating risks associated with payment processing systems and transactions. They analyze transaction data to detect fraudulent activities, ensure compliance with regulations, and develop strategies to minimize financial losses for organizations. Their work often involves using advanced analytics and risk management tools to monitor trends, investigate suspicious activities, and recommend improvements to payment processes.

What skills and qualifications are needed to be a payments risk analyst?

To thrive as a Payments Risk Analyst, you need strong analytical skills, knowledge of financial regulations, and experience in risk assessment, typically supported by a degree in finance, economics, or a related field. Familiarity with transaction monitoring systems, data analysis tools like SQL or Excel, and certifications such as CAMS or CFE are commonly required. Attention to detail, critical thinking, and effective communication are vital soft skills to excel in this role. These competencies are crucial for identifying and mitigating payment fraud, ensuring regulatory compliance, and maintaining the integrity of financial operations.

What challenges do payments risk analysts face in monitoring and mitigating transaction fraud?

Payments Risk Analysts often encounter the challenge of quickly identifying and responding to evolving fraud patterns while maintaining a seamless customer experience. The role requires balancing proactive risk detection with minimizing false positives, which can inadvertently affect legitimate transactions. Analysts must collaborate closely with data scientists, compliance teams, and customer service to continuously refine fraud detection models and stay updated on emerging threats. Staying adaptable and leveraging advanced analytics tools are key to success in this fast-paced environment.

Do payments risk analysts make good money?

Payments risk analysts typically earn a competitive salary that varies based on experience, location, and industry. Entry-level positions may start around $50,000 annually, while experienced analysts can earn over $100,000, especially with specialized skills in fraud detection and data analysis. Certifications such as Certified Fraud Examiner (CFE) can also enhance earning potential.

How much do payments risk analysts get paid?

Payments risk analysts typically earn a median annual salary of around $60,000 to $80,000, depending on experience, location, and industry. Entry-level positions may start lower, while experienced analysts with certifications can earn higher salaries, especially in financial services or technology sectors.

Is a payments risk analyst a good job?

A payments risk analyst is a role focused on identifying and mitigating fraud and financial risks in payment systems. It typically requires analytical skills, knowledge of financial regulations, and familiarity with risk management tools. The job offers opportunities for career growth in finance and technology sectors but can involve high-pressure situations and the need for continuous learning.

What are popular job titles related to Payments Risk Analyst jobs in Fairfield, NJ?

For Payments Risk Analyst jobs in Fairfield, NJ, the most frequently searched job titles are:

What cities near Fairfield, NJ are hiring for Payments Risk Analyst jobs?

Cities near Fairfield, NJ with the most Payments Risk Analyst job openings:

Payments Risk Analyst jobs near you
Infographic showing various Payments Risk Analyst job openings in Fairfield, NJ as of August 2026, with employment types broken down into 76% Full Time, 6% Part Time, and 18% Contract. Highlights an 76% In-person, 18% Hybrid, and 6% Remote job distribution, with an average salary of $85,856 per year, or $41.3 per hour.

Manager, Financial Planning & Analysis - Payments & Customer Service

Spotify

New York, NY • On-site

$115K - $151K/yr

Full-time

Medical, Retirement, PTO

Re-posted 21 days ago

Job description

Spotify is looking for a Manager to join our Finance team and serve as a dedicated FP&A partner for our global Payments and Customer Service functions. As Spotify continues to scale across markets and monetization models, payments sit at the heart of how we acquire, convert, and retain subscribers, while customer service shapes the experience and cost of supporting them. This role owns the financial lens on both ecosystems.

This is a high-impact, partner-facing finance role responsible for the payments and customer service forecast processes, the financial evaluation of payment partner and processor deals, the pipeline of payment optimization proposals, revenue protection and payment-cost assurance, and the modeling of contact center labor needs. You will partner with Payments, Customer Service, Subscriptions, Risk, Data, Financial Engineering, Accounting, and Business leadership to translate complex operational economics into clear financial narratives, build the models that inform decisions, and govern performance against plan.

What You'll Do
  • Payments Forecast Process Own the end-to-end payments forecast - including processing fees, vendor mix, and refunds - across monthly, quarterly, and annual planning cycles. Build and maintain driver-based models, analyse variances against forecast, and clearly explain the underlying drivers to leadership.
  • Payment Deal Making & Partner Value Serve as the finance lead on payment partner, processor, and payment-method agreements. Model deal economics, pricing tiers, volume commitments, and incentive structures; quantify margin and cash-flow impact; and maximise the value of strategic partnerships while driving cost efficiencies at scale alongside Payments, Legal, and Business Development.
  • Payment Optimisation & AI/ML Build business cases for payment optimisation initiatives - routing, retry logic, local payment methods, fee reduction, and authorisation-rate improvements, including ML-driven optimisation. Size the opportunity, define success metrics, and track realised impact against the original investment case.
  • Checkout Flow Build business cases for checkout experience investments, partnering with Product and Engineering to evaluate the financial impact of flow changes on conversion, payment success rates, and subscriber acquisition costs.
  • Regional & Local Payment Methods Partner with regional payments leads to evaluate the economics of local payment methods, prioritise market-level investments, and align regional performance with global priorities.
  • Revenue Protection & Risk Provide the financial lens on revenue protection and payment risk - fraud, authentication, disputes and chargebacks, and reselling - quantifying the trade-off between loss mitigation, margin, and genuine-user experience, and supporting the business case for risk and regulatory readiness.
  • Payment Cost Assurance Partner with Financial Engineering and Data Science to verify and reconcile payment fees, detect fee anomalies, and build the automation, tooling, and alerting that improve cost visibility and forecasting accuracy.
  • Customer Service Forecast Process Own the customer service forecast across monthly, quarterly, and annual planning cycles - contact volumes, channel mix, cost-to-serve, and outsourced and in-house support spend. Analyse variances against plan and clearly explain the drivers to leadership.
  • Contact Centre Labour & Vendor Management Build and maintain workforce models that translate forecasted contact volumes, handle times, and service-level targets into headcount, staffing, and labour cost. Manage the economics of the BPO/vendor portfolio and site mix across geographies, and run scenario analysis for ramp-ups, seasonality, capacity, and efficiency initiatives.
  • Service Automation & Deflection Economics Quantify the financial impact of self-service, automation, and AI-driven deflection on contact volume and cost-to-serve, and build the business cases that balance efficiency against customer experience.
  • Performance Governance Establish and own the reporting infrastructure for payments and customer service. Develop and track KPIs covering cost of payments, acceptance rates, cost-to-serve, and the long-term unit economics of both functions.
  • Strategic Partnership Act as the primary finance partner to the Payments and Customer Service organisations, providing scenario analysis and decision support on roadmap prioritisation, market expansion, staffing strategy, and infrastructure investment.
  • Cross-Functional Leadership Partner with Data and Engineering teams to improve forecasting accuracy and cost visibility, and translate operational data into financial insight for non-technical stakeholders across Spotify.
Who You Are
  • Experienced Finance Professional: 5+ years in FP&A, Corporate Development, Investment Banking, or strategic finance. Experience in payments, fintech, subscriptions, customer service/contact centre operations, or other transaction- and labour-intensive businesses is highly preferred.
  • Sophisticated Modeller: You build dynamic, driver-based models that handle complex variables - fee structures, payment-method mix, FX, fraud and dispute rates, contact volumes, handle times, and staffing requirements - and distil them into the assumptions that matter most for a decision.
  • Deal-Oriented: You can structure and evaluate commercial agreements, pressure-test pricing and incentive terms, and clearly articulate trade-offs to senior stakeholders.
  • Clear Communicator & Influencer: You have a sharp eye for detail and the ability to influence senior stakeholders across Finance and the business through clear, data-driven narratives and investment cases.
  • Operational Mindset: You are comfortable navigating ambiguity and building processes from scratch in a fast-paced, flat organisational structure.
  • Systems Fluency: Comfortable with automated reporting and planning tools (NetSuite/Adaptive, Workday Financials), strong SQL or data fluency, and a track record of leveraging AI and ML to drive analytical throughput and optimisation.
Where You'll Be
  • This role is based in London or New York.
  • We offer flexibility to work where you work best, with 2-3 days per week in the office.
  • Collaboration hours align to the EST time zone.
The United States base range for this position is $117,677-$168,111, plus equity. The benefits available for this position include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, paid flexible holidays, and paid sick leave. These ranges may be modified in the future.

Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what's playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It's in our differences that we will find the power to keep revolutionizing the way the world listens.
 
At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we're here to support you in any way we can.
 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice
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