12 of 12 Monte Carlo Method Jobs

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 ...

Python skills coupled with 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 ...

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 ...

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 ...

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 ...

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 ...

implementation, and optimizing communication infrastructure placements. You will also analyze these systems using parametric studies, carpet plots, Design of Experiments (DOE) tests, and Monte Carlo-based probabilistic analysis. Required Tool Proficiency: Scenario Generation: You must be proficient with MAK-ONE (VR-Forces & VR-Vantage) and EMANE ...