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Financial Engineering Jobs in New York (NOW HIRING)

Bachelor's degree in Computer Science, Mathematics, Operations Research, Financial Engineering, or a relevant quantitative field SOFT SKILLS * Self‑driven with strong initiative -- proactively ...

Finance Engineer

Elizabeth, NJ · On-site

$150 - $200/hr

This role covers the full range of FP&A responsibilities - modeling, reporting, budgeting, and ... Engineering & Systems * Treat the finance stack as something to improve, not just operate

Finance Engineer

Elizabeth, NJ · On-site

$150 - $200/hr

This role covers the full range of FP&A responsibilities - modeling, reporting, budgeting, and ... Engineering & Systems * Treat the finance stack as something to improve, not just operate

Showing results 21-40

Financial Engineering information

See New York salary details

$83.1K

$121.2K

$148.8K

How much do financial engineering jobs pay per year?

As of Sep 8, 2026, the average yearly pay for financial engineering in New York is $121,232.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,400.00 and $136,200.00 per year, depending on experience, location, and employer.

What is financial engineering?

Financial engineering is the application of mathematical techniques, computer science, and statistical methods to solve problems and create innovative solutions in finance. Professionals in this field develop new financial products, manage risk, and optimize investment strategies using quantitative models. Financial engineers often work in banks, investment firms, hedge funds, or financial technology companies, helping organizations manage complex financial systems and products. The discipline combines finance, mathematics, statistics, and programming to address challenges in areas like derivatives pricing, risk management, and portfolio optimization.

What are some common challenges faced by financial engineers when implementing quantitative models in real-world financial institutions?

Financial engineers often encounter challenges such as aligning complex quantitative models with existing IT infrastructure and ensuring the models comply with regulatory requirements. Additionally, translating theoretical models into practical, scalable solutions that can handle large volumes of real-time data requires close collaboration with software developers and risk managers. Effective communication with non-technical stakeholders is also crucial, as financial engineers must explain model assumptions and results to decision-makers from diverse backgrounds.

What are the key skills and qualifications needed to thrive as a financial engineer, and why are they important?

To thrive as a Financial Engineer, you need a strong background in quantitative analysis, mathematics, programming, and finance, typically supported by a relevant degree such as financial engineering, mathematics, or computer science. Expertise in programming languages like Python, R, or C++, as well as familiarity with financial modeling software and risk management systems, is essential. Strong problem-solving, analytical thinking, and communication skills set top performers apart in this role. These skills are crucial for designing innovative financial products, managing complex risks, and translating quantitative insights into actionable business strategies.

What is the difference between Financial Engineering vs Quantitative Analyst?

AspectFinancial EngineeringQuantitative Analyst
Required CredentialsDegree in Financial Engineering, Mathematics, or related fields; often certifications like CQFDegree in Finance, Mathematics, or Statistics; certifications like CFA or CQF are common
Work EnvironmentFinancial institutions, hedge funds, investment banks; focus on product development and risk managementTrading desks, asset management firms; focus on data analysis and model development
Employer & Industry UsageUsed in risk management, derivatives pricing, and structured productsUsed in trading strategies, portfolio management, and risk assessment

Financial Engineering and Quantitative Analysts often share similar educational backgrounds and work in related financial sectors. While Financial Engineers focus on creating financial products and managing risks through complex models, Quantitative Analysts primarily analyze data to inform trading and investment decisions. Both roles require strong quantitative skills and often overlap in financial institutions.

What is the work of a financial engineer?

A financial engineer develops mathematical models and uses quantitative techniques to analyze and manage financial risks, design trading strategies, and create financial products. They often work with programming tools like Python or C++ and require strong skills in mathematics, finance, and computer science. Their work supports decision-making in investment banks, hedge funds, and financial institutions.

What jobs do financial engineers get?

Financial engineers typically work as quantitative analysts, risk managers, derivatives traders, or financial modelers in banking, investment firms, hedge funds, and insurance companies. They use skills in mathematics, programming, and financial theory to develop models and strategies for trading, risk assessment, and asset management.

What are popular job titles related to Financial Engineering jobs in New York?

For Financial Engineering jobs in New York, the most frequently searched job titles are:

What job categories do people searching Financial Engineering jobs in New York look for?

The top searched job categories for Financial Engineering jobs in New York are:

What cities in New York are hiring for Financial Engineering jobs?

Cities in New York with the most Financial Engineering job openings:

Infographic showing various Financial Engineering job openings in New York as of September 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Hybrid job distribution, with an average salary of $121,232 per year, or $58.3 per hour.

Manager, Financial Planning & Analysis - Payments & Customer Service

Manhattan, NY • On-site

$125 - $150/hr

Other

Medical, Retirement, PTO

Posted 7 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.

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