- Company Name
- Lithe Transformation
- Job Title
- Quantitative Developer
- Job Description
-
**Job Title:** Quantitative Developer – Pricing & Risk Technology
**Role Summary:**
Design, develop, and maintain Python-based pricing and risk libraries that support real‑time and end‑of‑day analytics for global trading desks. Implement and optimise standard and structured derivatives models, ensuring consistency across valuation, risk, and front‑office systems. Act as the technical bridge between quantitative researchers, data engineers, and business stakeholders.
**Expectations:**
- Deliver robust, production‑grade code for pricing and risk workflows within a cloud‑enabled, CI/CD‑driven environment.
- Maintain high standards of numerical stability, performance, and diagnostic transparency.
- Collaborate cross‑functionally to translate research into scalable implementations and support end‑users globally.
**Key Responsibilities:**
- Develop and extend Python libraries for vanilla and structured options (commodities, equities).
- Implement and calibrate models: Black–Scholes, Heston, SABR, Monte Carlo for structured instruments such as APOs, CSOs, ULDs, P1X.
- Design volatility surface calibration pipelines (interpolation, extrapolation, smoothing).
- Manage market‑data, proxy logic, and curve handling for valuation and risk analytics.
- Enhance model performance, numerical stability, and diagnostic visibility.
- Write regression tests, benchmarks, and participate in CI/CD (Git, Jenkins, Docker/Kubernetes, AWS).
- Serve as subject‑matter expert on pricing models and valuation logic for risk and trading teams worldwide.
**Required Skills:**
- Expert Python programming with NumPy, SciPy, Pandas; strong numerical computing experience.
- Deep understanding of derivatives pricing theory, volatility modelling, stochastic calculus, calibration, curve bootstrapping, Greeks, VaR.
- Experience implementing commodity or equity derivatives pricing models.
- Familiarity with cloud compute (AWS ECS, Lambda, S3), DevOps tools (Git, Jenkins, Docker, Kubernetes).
- Knowledge of C++ or C# beneficial for model integration.
- Excellent analytical reasoning, problem‑solving, and communication skills.
**Required Education & Certifications:**
- Advanced degree (Master’s or PhD) in Mathematics, Physics, Financial Engineering, or a quantitatively rigorous field.
- Minimum 5–10 years of quantitative development or model engineering experience in trading, banking, or commodities.
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Central london, United kingdom
On site
Mid level
28-11-2025