23 of 23 Monte Carlo Method Jobs

layer: new business units, platforms, use cases, and stakeholders. Build technical champions. Identify and develop the advocates inside each account who will carry Monte Carlo into the next budget cycle, platform migration, or executive review. Run briefings, workshops, and architecture reviews that position our platform … infrastructure. Drive POVs that convert. When an account wants to extend Monte Carlo into a new platform, region, or team, you design the proof of value, set success criteria, and deliver a result that accelerates the commercial close. Own technical account strategy. Map the whitespace ...

Trading Systems Architecture Architect end-to-end front-to-back trading workflows, from deal capture and position management through risk analytics (VaR, Greeks, Monte Carlo, stress testing), P&L attribution, settlement, invoicing, confirmations and regulatory reporting (REMIT, EMIR, MiFID II, ACER). Design and govern … Proven track record of defining and delivering enterprise-level architecture for front-to-back trading platforms, including trade capture, risk management (VaR, Greeks, Monte Carlo, stress testing), P&L attribution, settlement, confirmations and regulatory reporting. Expert understanding of integration architecture in high-performance trading environments including ...

Trading Systems Architecture Architect end-to-end front-to-back trading workflows, from deal capture and position management through risk analytics (VaR, Greeks, Monte Carlo, stress testing), P&L attribution, settlement, invoicing, confirmations and regulatory reporting (REMIT, EMIR, MiFID II, ACER). Design and govern … Proven track record of defining and delivering enterprise-level architecture for front-to-back trading platforms, including trade capture, risk management (VaR, Greeks, Monte Carlo, stress testing), P&L attribution, settlement, confirmations and regulatory reporting. Expert understanding of integration architecture in high-performance trading environments including ...

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/ ...

implementing advanced mathematical and statistical models Deriving new quantitative models and enhancing existing solutions to improve business performance Applying complex statistical distributions and Monte Carlo simulation techniques to solve challenging modelling problems Leading quantitative modelling initiatives from concept through to production deployment Backtesting, validating and refining … record of delivering high-impact quantitative models Deep expertise in mathematical and statistical modelling techniques Strong understanding of probability, complex statistical distributions and Monte Carlo simulations Advanced Python skills for modelling, analysis and data manipulation Experience with model validation, backtesting and performance evaluation Strong understanding ...

Responsibilities : · Risk Identification: Proactively identify and assess potential project risks through engaging workshops and team discussions. · Risk Analysis: Conduct quantitative risk analysis using Monte Carlo simulation and reference class forecasting to inform decision-making. · Mitigation Planning: Develop and recommend strategies to minimise risk impact, seamlessly integrating … major infrastructure projects. · In-depth knowledge of project risk management principles, frameworks, and methodologies. · Proficiency in conducting bottom-up quantitative risk analysis, including Monte Carlo simulation and top-down techniques. · Familiarity with project risk management software (e.g., Primavera, Palisade). · Strong analytical skills that drive data ...

Responsibilities : · Risk Identification: Proactively identify and assess potential project risks through engaging workshops and team discussions. · Risk Analysis: Conduct quantitative risk analysis using Monte Carlo simulation and reference class forecasting to inform decision-making. · Mitigation Planning: Develop and recommend strategies to minimise risk impact, seamlessly integrating … major infrastructure projects. · In-depth knowledge of project risk management principles, frameworks, and methodologies. · Proficiency in conducting bottom-up quantitative risk analysis, including Monte Carlo simulation and top-down techniques. · Familiarity with project risk management software (e.g., Primavera, Palisade). · Strong analytical skills that drive data ...

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 ...

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 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 ...

Senior Data Engineer or in an equivalent technical leadership role in data quality, observability, or governance. Deep knowledge of data observability frameworks (Monte Carlo, Soda, or equivalent) and data validation tools (Great Expectations, etc.). Deep understanding of Data Products principles and experience applying them ...

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 ...

Staff Data Engineer or in an equivalent technical leadership role in data quality, observability, or governance.Deep knowledge of data observability frameworks (Monte Carlo, Soda, or equivalent) and data validation tools (Great Expectations, DBT tests, etc.).Deep understanding of data-as-a-product principles and experience applying ...

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 ...

managers and engineers It’s a bonus if you are familiar with FX or financial markets experience Term structure modelling, stochastic calculus or Monte Carlo methods Interest rate curve bootstrapping Algorithmic execution experience Data lake or warehouse experience (Snowflake, Iceberg, Spark etc.) We’re people without ...

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 ...

Products: Strong OTC derivatives expertise, specifically with variance swaps, volatility swaps, and knocking knockouts. Execution: Proven ability to implement advanced numerical methods (e.g., Monte Carlo) and hit the ground running. Apply If you are a senior quant engineer who can translate complex math into high-performance ...

Monte Carlo is seeking a seasoned pre‐sales leader to own the technical sales cycle for expansion within strategic accounts across the EMEA region. You will partner with Strategic Account Executives to convert deployed usage into larger, multi‐year commitments. This role requires navigating complex procurement ...

Kanban and flow‐based delivery management . Experience using delivery metrics including WIP, lead time, cycle time and throughput analysis. Practical application of Monte Carlo forecasting and confidence‐based planning techniques. Experience using Jira, Actionable Agile or similar tooling for forecasting and delivery insight. Coaching teams ...

Kanban and flow-based delivery management, including WIP management, lead time, cycle time, throughput analysis and service-level expectations Practical application of Monte Carlo forecasting to improve delivery predictability and confidence-based planning Experience implementing forecasting approaches using Jira, Actionable Agile or similar tooling Coaching ...