13 of 13 Monte Carlo Method Jobs

managers, hedge funds, and other sophisticated market participants. Responsibilities: Influence the product roadmap for portfolio risk analytics features, including Analytical/Historical/Monte Carlo VaR, factor-based performance attribution, and stress/scenario testing. Collaborate with quantitative developers to design, validate, and implement factor risk … . 6+ years’ experience in market risk analytics, preferably in product management, quantitative analysis, or risk technology roles. Strong understanding of Historical/Monte Carlo VaR, factor attribution, stress testing, and related statistical/financial methodologies. Experience with derivatives pricing models, stochastic processes, portfolio construction/ ...

code basics (Terraform) Streaming and big data exposure (Kafka, Kinesis, Spark, Flink) is a plus Data quality and observability tooling (Great Expectations, Monte Carlo, Soda, dbt tests) is a plus Engineering & Soft Skills: Strong software engineering discipline—pipelines are products, not scripts Data quality mindset ...

Python skills and experience working in modern cloud-based data environments. Hands-on experience with data observability tools such as Grafana, Monte Carlo, or Acceldata, and data governance/quality platforms like Informatica, Collibra or Microsoft Purview is highly desirable. Experience within the Azure ecosystem (data ...

Python skills and experience working in modern cloud-based data environments. Hands-on experience with data observability tools such as Grafana, Monte Carlo, or Acceldata, and data governance/quality platforms like Informatica, Collibra or Microsoft Purview is highly desirable. Experience within the Azure ecosystem (data ...

skills Cloud: GCP Warehousing: BigQuery/Snowflake Orchestration: Airflow Backend: Python, SQL, Shell Languages: Scala/Java DevOps: Terraform, Docker, Kubernetes Observability: Monte Carlo BI: Looker AI/ML: MLOps London | 12 Months Contract |£400 a day Inside IR35 If you want to work ...

clear SLOs/SLA, observability, reliability engineering practices, and tight integration into trading/risk platforms. Provide technical leadership and mentorship; conduct code/method reviews, establish research engineering best practices (testing, CI/CD, reproducibility), and develop team capability. Communicate complex quantitative concepts to non technical audiences; influence … curve building (multi curve frameworks), volatility surface modelling/calibration (e.g., SABR, Heston, local/stochastic volatility), and numerical methods (PDE/FDM, Monte Carlo, adjoint/automatic differentiation). Experience with market risk, time series/stress analytics, model risk governance, and regulatory expectations ...

clear SLOs/SLA, observability, reliability engineering practices, and tight integration into trading/risk platforms. Provide technical leadership and mentorship; conduct code/method reviews, establish research engineering best practices (testing, CI/CD, reproducibility), and develop team capability. Communicate complex quantitative concepts to non-technical audiences; influence … curve building (multi-curve frameworks), volatility surface modeling/calibration (e.g., SABR, Heston, local/stochastic volatility), and numerical methods (PDE/FDM, Monte Carlo, adjoint/automatic differentiation). Experience with market risk, time-series/stress analytics, model risk governance, and regulatory expectations ...

permanent. What You'll Do: Build and maintain scalable data pipelines for BigQuery using Cloud Composer and Airflow; Provide observability and monitoring using Monte Carlo and Looker as well as operational tools such as NewRelic and Splunk, driving reliability, data quality, data quality and robustness; Build ...

skills in: Python (essential) C++/Java/C# (strongly preferred) Experience with: Object-oriented design and software engineering best practices Numerical methods (Monte Carlo, PDEs, stochastic calculus) Data structures, algorithms, and performance optimisation Familiarity with: Quant libraries (e.g., QuantLib) Cloud platforms or distributed computing (nice ...

C++ , and/or Python for numerically intensive code. Java and pricing engine experience is highly preferred. Numerical Expertise: Implement advanced methods including Monte Carlo, Tree/lattice, and PDE approaches. Analytics & Curves: Build core libraries for valuation, sensitivities, and XVA, alongside robust curve construction/ ...

Library Evolution: Build and evolve core analytics libraries used for valuation, sensitivities, scenarios, and XVA. Advanced Numerical Implementation: Implement advanced numerical techniques including Monte Carlo methods (with variance reduction), Tree/lattice methods, PDE approaches, and curve construction (bootstrapping/interpolation). High-Performance Engineering: Deliver ...

Responsibilities Greenfield Ownership: Design, code, calibrate, and roll out pricing and risk frameworks for complex OTC derivatives from scratch. Numerical Frameworks: Implement robust Monte Carlo methods, Tree/lattice methods, and PDE approaches. Curve Engineering: Manage multi-curve setups, sophisticated interpolation, and bootstrapping frameworks. Deep Validation ...

exotic derivatives, OTC market behaviour, pricing conventions, curve frameworks, sensitivities, calibration techniques, stress testing, and real-world quantitative modelling constraints. Strong experience with Monte Carlo methods, PDE approaches, tree/lattice models, and advanced numerical techniques is expected. The current team consists of quant developers ...