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dataroles

Quantitative Analyst, Front Office (Calypso)

Nasdaq Open
Paris Full-time Mid-level Data Science

At a glance

Mid-level Data Science role at Nasdaq. Paris · full-time.

Pay not stated Data Science salary

RoleData Science
SeniorityMid-level
LocationParis
EmploymentFull-time
PostedSep 28, 2026
Role brief

dataroles summary, based on the employer's posting.

What you'll do

  • Build and maintain pricing, risk and XVA models spanning rates, FX, credit, equities and commodities
  • Turn mathematical model specifications into tested production code, taking each model from derivation through deployment
  • Work with client quants and traders to calibrate models, check their performance and extend them to new products and markets
  • Improve model speed with engineering teams using vectorization, parallel computing and adjoint sensitivity methods
  • Support AI and machine-learning work on model speed, calibration and anomaly detection, and document models for validation reviews

What you bring

  • A PhD or equivalent research background in a quantitative discipline such as mathematics, physics or engineering
  • Up to five years of derivatives analytics work as a quant analyst, in any asset class
  • Strong coding skills in Java, C++ or C#, plus experience with version control and code review
  • Sound knowledge of stochastic calculus, numerical methods such as Monte Carlo or PDEs, and derivatives pricing

Who this fits

This role suits a quantitative analyst who wants to take models from mathematical design into production and work directly with clients, traders and engineers. It is based in Paris and requires at least three office days each week.

From the employer

As a Quantitative Analyst reporting to Senior Quantitative Analyst, you'll play a critical role in designing, implementing, and productionizing the pricing and risk models that power our clients' trading desks globally.

You'll thrive in this position if you're analytically rigorous, passionate about building production-grade analytics, and energized by working across asset classes in a fast-paced, high-impact environment.

Nasdaq Calypso delivers mission-critical risk, regulatory, and trading technology to some of the world's largest financial institutions - and this team sits at the heart of that work.

Key Responsibilities

  • Develop and maintain pricing, risk, and XVA models across rates, FX, credit, equity, and commodities asset classes.

  • Translate mathematical specifications into high-performance, well-tested production code, owning models end-to-end from derivation through to deployment.

  • Partner directly with clients' quantitative analysts and traders to calibrate, validate, and extend models to new products and markets.

  • Collaborate with Engineering teams on performance optimization, including vectorization, parallel compute, and adjoint sensitivity techniques.

  • Contribute to AI/ML initiatives focused on model acceleration, calibration, and anomaly detection, and produce clear technical documentation for model validation reviews.

Required Qualifications

  • PhD (or equivalent research experience) in Mathematics, Physics, Engineering, Computational Finance, or a related quantitative discipline.

  • Up to 5 years of experience in derivatives analytics as a Quantitative Analyst, covering any asset class.

  • Strong development proficiency in Java, C++, or C#, with experience in collaborative development environments including version control and code review practices.

  • Solid grounding in stochastic calculus, numerical methods (Monte Carlo, PDE, finite difference), and derivative pricing theory.

  • Clear communicator with experience working across global, cross-functional teams including traders, engineers, and clients.

Preferred Qualifications

  • Experience with algorithmic differentiation libraries or exposure to XVA, regulatory capital frameworks, or initial/variation margin calculation engines.

  • Applied ML/AI in pricing, calibration, or risk contexts using frameworks such as PyTorch, JAX, or scikit-learn.

  • Cloud-native development experience and familiarity with contributing to a software provider or sell-side production analytics library.

This position is based in Paris and offers a hybrid work environment with at least 3 days per week in office.

Benefits & Rewards

We offer a competitive, well-rounded rewards package that supports you and your family - inside and outside work. Actual pay depends on your skills, experience, education, and location. In addition to base pay, we offer short-term incentives (bonus or commission) and long-term incentives (equity), where applicable, as well as the following benefits:

  • Competitive base salary

  • Annual bonus

  • Annual equity grant

  • Employee Stock Purchase Plan offering discounted company shares

  • Pension plan with Nasdaq contribution

  • 6 additional days off per year

  • Extra vacation time based on tenure

  • Work from (almost) anywhere – up to 20 days/year

  • Paid time off to volunteer

  • Health insurance

  • 24/7 mental health support for you and your family

  • Global mentoring program

  • Unlimited access to e-learning platforms

  • Hybrid work setup

  • Modern and comfortable work environment with fresh fruit, snacks, and weekly fika breaks.

Learn more on our Nasdaq Benefits & Rewards Career Page.

Come as You Are

Nasdaq is an equal opportunity employer. We welcome applications from candidates of all backgrounds and identities.

We are committed to fostering an inclusive workplace where diverse perspectives, experiences, and identities are valued and celebrated.

We ensure that individuals with disabilities are provided with reasonable accommodation throughout the hiring process.

Opportunity

Data Science work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Science

Find me work

By the team behind dataroles.

Find me work
Opportunity

Data Science work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind dataroles.