MerQube
Derivative Quant Analyst
New York, NY · Mid
Stay score
odds of building a lasting career here
Sponsors, but it's cap-subject — you still face the weighted lottery (~45% per draw at Level III). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →H-1B wage level
the lottery is wage-weighted — each level is one more entry
$8,278 more — $138,278 — moves this role to Level III and 3 lottery entries. That figure is inside the range the employer already advertised.
Based on the DOL prevailing wage for this occupation and worksite, a base salary of $138,278 would place this position at wage Level III. That figure is within the posted range, and I'd like to target it. This role classifies under "Financial Specialists, All Other" for prevailing-wage purposes.
DOL prevailing wage, 2026-27 wage year · Financial Specialists, All Other (13-2099) · New York-Newark-Jersey City, NY-NJ. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
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About the role
- We are looking for our next Derivative Quant Analyst based in New York.
Responsibilities
- Research, develop, and continuously improve implied volatility and pricing frameworks for options and exotic derivatives.
- You will build deep expertise across implied volatility modeling, no-arbitrage surface construction, and derivative pricing, developing intuition that spans a wide range of modeling approaches and payoff structures.
- Collaborate with the Financial Engineering team to develop MerQube branded financial engines and indexing strategies for major financial institutions.
- A team that feels like home: we're building a community-first culture
- we're building a community-first culture
Requirements
- Master's degree in Finance or a related quantitative field (Mathematics, Data Science, Economics, Computer Science or Engineering), or a Bachelor's degree with equivalent work experience.
- Proficiency in Python programming, with a focus on financial data management.
- Minimum of 2-3 years of experience in equity derivatives pricing and quantitative research, ideally as a sell-side quant, with hands-on exposure to volatility modelling, pricing model implementation, and industry-standard market conventions.
- Strong interest in financial markets and the intersection of software and quantitative finance.
- Excellent communication skills and the ability to collaborate effectively with both clients and internal teams.
- Our Commitment:
- At MerQube, we foster a collaborative, fast-moving environment where team members can grow and expand their technical, financial, and leadership skills. We prioritize wellness, work-life balance, and offer flexible working arrangements. We celebrate diversity and welcome team members from all backgrounds, encouraging continuous learning and career growth while playing a key role in transforming the financial industry.
Skills
- MerQube is an innovative fintech firm, leading the development of cutting-edge technology for indexing and rules-based investing.
Compensation
- In accordance with New York's pay transparency law, the annual base salary range for this position is $130,000-$180,000.
Benefits
- Benefits that actually have your back: top-tier medical, dental, vision, and more
- Your wellbeing, prioritized: real investment in health, wellness, and work-life balance
- Time to recharge: generous PTO, holidays, and sick time, because rest fuels great work
- This range reflects base salary only and does not include bonus, equity, or benefits.
- Work where you work best: flexible arrangements, including hybrid options
- flexible arrangements, including hybrid options
Company info
- Position Overview: We are looking for our next Derivative Quant Analyst based in New York.
- Our Commitment: At MerQube, we foster a collaborative, fast-moving environment where team members can grow and expand their technical, financial, and leadership skills.
This listing is sourced directly from MerQube's careers page and normalized into a canonical job model.