1 to 25 of 33 Permanent Monte Carlo Method Jobs in London

for sports betting, with a primary focus on deriving new markets and enhancing existing offerings. Possess a deep understanding of complex statistical distributions and leverage techniques such as Monte Carlo simulations in model development. Rigorously back test and validate models to ensure their robustness, accuracy, and profitability in real-world betting scenarios. Drive and lead quantitative … impactful quantitative models in a production environment. Deep expertise in mathematical and statistical modelling, specifically applied to sports betting, including a strong understanding of complex statistical distributions and Monte Carlo simulations. Highly proficient in Python for all modelling, analysis, and data manipulation work. Strong experience in back testing, validation, and performance evaluation of quantitative models. Solid More ❯

for sports betting, with a primary focus on deriving new markets and enhancing existing offerings. Possess a deep understanding of complex statistical distributions and leverage techniques such as Monte Carlo simulations in model development. Rigorously back test and validate models to ensure their robustness, accuracy, and profitability in real-world betting scenarios. Drive and lead quantitative … impactful quantitative models in a production environment. Deep expertise in mathematical and statistical modelling, specifically applied to sports betting, including a strong understanding of complex statistical distributions and Monte Carlo simulations. Highly proficient in Python for all modelling, analysis, and data manipulation work. Strong experience in back testing, validation, and performance evaluation of quantitative models. Solid More ❯

for sports betting, with a primary focus on deriving new markets and enhancing existing offerings. Possess a deep understanding of complex statistical distributions and leverage techniques such as Monte Carlo simulations in model development. Rigorously back test and validate models to ensure their robustness, accuracy, and profitability in real-world betting scenarios. Drive and lead quantitative … impactful quantitative models in a production environment. Deep expertise in mathematical and statistical modelling, specifically applied to sports betting, including a strong understanding of complex statistical distributions and Monte Carlo simulations. Highly proficient in Python for all modelling, analysis, and data manipulation work. Strong experience in back testing, validation, and performance evaluation of quantitative models. Solid More ❯

for sports betting, with a primary focus on deriving new markets and enhancing existing offerings. Possess a deep understanding of complex statistical distributions and leverage techniques such as Monte Carlo simulations in model development. Rigorously back test and validate models to ensure their robustness, accuracy, and profitability in real-world betting scenarios. Drive and lead quantitative … impactful quantitative models in a production environment. Deep expertise in mathematical and statistical modelling, specifically applied to sports betting, including a strong understanding of complex statistical distributions and Monte Carlo simulations. Highly proficient in Python for all modelling, analysis, and data manipulation work. Strong experience in back testing, validation, and performance evaluation of quantitative models. Solid More ❯

FRTB, and CCAR is highly advantageous. Solid mathematical finance and advanced statistical analysis skills. Profound knowledge of probability theory and stochastic calculus. Extensive familiarity with Numerical Analysis and Monte-Carlo methods. Proven experience developing robust software for Windows and Linux environments. Excellent command of scripting using UNIX Shell (ksh, bash, etc.), Python, and VBA. Knowledge of More ❯

for near real-time metadata synchronization. Data Governance Enablement — Define RBAC, data ownership models, workflows, and certification for golden datasets. Data Quality & Observability — Integrate DQ/DO tools ( Monte Carlo, Anomalo, Soda ) to visualize trust metrics and compliance dashboards. Collaboration & Adoption — Mentor teams, document best practices, and drive adoption across engineering and business units. 🧠 What You More ❯

for near real-time metadata synchronization. Data Governance Enablement — Define RBAC, data ownership models, workflows, and certification for golden datasets. Data Quality & Observability — Integrate DQ/DO tools ( Monte Carlo, Anomalo, Soda ) to visualize trust metrics and compliance dashboards. Collaboration & Adoption — Mentor teams, document best practices, and drive adoption across engineering and business units. 🧠 What You More ❯

for near real-time metadata synchronization. Data Governance Enablement — Define RBAC, data ownership models, workflows, and certification for golden datasets. Data Quality & Observability — Integrate DQ/DO tools (Monte Carlo, Anomalo, Soda) to visualize trust metrics and compliance dashboards. Collaboration & Adoption — Mentor teams, document best practices, and drive adoption across engineering and business units. 🧠 What You More ❯

for near real-time metadata synchronization. Data Governance Enablement — Define RBAC, data ownership models, workflows, and certification for golden datasets. Data Quality & Observability — Integrate DQ/DO tools (Monte Carlo, Anomalo, Soda) to visualize trust metrics and compliance dashboards. Collaboration & Adoption — Mentor teams, document best practices, and drive adoption across engineering and business units. 🧠 What You More ❯

production, enabling advanced users such as ML and analytics engineers. Hands-on experience with modern data stack tools - Airflow, DBT, Databricks, and data catalogue/observability solutions like Monte Carlo, Atlan, or DataHub. Solid understanding of cloud environments (AWS or GCP), including IAM, S3, ECS, RDS, or equivalent services. Experience rolling out data governance and observability More ❯

Develop and deliver sophisticated mathematical and statistical models aimed at identifying new opportunities and refining existing market strategies. Utilise strong knowledge of statistical theory, including complex distributions and Monte Carlo techniques, to design and optimise modelling approaches. Test, validate, and benchmark models to ensure they perform reliably under a range of real-world conditions. Take ownership More ❯

Develop and deliver sophisticated mathematical and statistical models aimed at identifying new opportunities and refining existing market strategies. Utilise strong knowledge of statistical theory, including complex distributions and Monte Carlo techniques, to design and optimise modelling approaches. Test, validate, and benchmark models to ensure they perform reliably under a range of real-world conditions. Take ownership More ❯

Develop and deliver sophisticated mathematical and statistical models aimed at identifying new opportunities and refining existing market strategies. Utilise strong knowledge of statistical theory, including complex distributions and Monte Carlo techniques, to design and optimise modelling approaches. Test, validate, and benchmark models to ensure they perform reliably under a range of real-world conditions. Take ownership More ❯

Develop and deliver sophisticated mathematical and statistical models aimed at identifying new opportunities and refining existing market strategies. Utilise strong knowledge of statistical theory, including complex distributions and Monte Carlo techniques, to design and optimise modelling approaches. Test, validate, and benchmark models to ensure they perform reliably under a range of real-world conditions. Take ownership More ❯

passion for data-driven problem solving, innovation, and continuous improvement. ✨ Nice-to-haves: Experience with data orchestration tools (Airflow, Prefect). Knowledge of data observability or cataloguing tools (Monte Carlo, OpenMetadata). Familiarity with large-scale consumer data or survey environments. More ❯

passion for data-driven problem solving, innovation, and continuous improvement. ✨ Nice-to-haves: Experience with data orchestration tools (Airflow, Prefect). Knowledge of data observability or cataloguing tools (Monte Carlo, OpenMetadata). Familiarity with large-scale consumer data or survey environments. More ❯

passion for data-driven problem solving, innovation, and continuous improvement. Nice-to-haves: Experience with data orchestration tools (Airflow, Prefect). Knowledge of data observability or cataloguing tools (Monte Carlo, OpenMetadata). Familiarity with large-scale consumer data or survey environments. More ❯

passion for data-driven problem solving, innovation, and continuous improvement. ✨ Nice-to-haves: Experience with data orchestration tools (Airflow, Prefect). Knowledge of data observability or cataloguing tools (Monte Carlo, OpenMetadata). Familiarity with large-scale consumer data or survey environments. More ❯

production, enabling advanced users such as ML and analytics engineers. Hands-on experience with modern data stack tools - Airflow, DBT, Databricks, and data catalogue/observability solutions like Monte Carlo, Atlan, or DataHub. Solid understanding of cloud environments (AWS or GCP), including IAM, S3, ECS, RDS, or equivalent services. Experience implementing Infrastructure as Code (Terraform) and More ❯

designing, building, and scaling data platforms in production environments. Hands-on experience with big data technologies such as Airflow, DBT, Databricks, and data catalogue/observability tools (e.g. Monte Carlo, Atlan, Datahub). Knowledge of cloud infrastructure (AWS or GCP) - including services such as S3, RDS, EMR, ECS, IAM. Experience with DevOps tooling, particularly Terraform and More ❯

required: 3+ years' experience within predictive modelling, machine learning, and probability theory. Ideally this would be within sports or gaming/betting industries. Understanding of techniques such as Monte Carlo simulation, Bayesian modelling, GLMs, mixed effects models, time series forecasting etc Strong programming ability, preferably in Python SQL and relational databases The company offer some great More ❯

required: 3+ years' experience within predictive modelling, machine learning, and probability theory. Ideally this would be within sports or gaming/betting industries. Understanding of techniques such as Monte Carlo simulation, Bayesian modelling, GLMs, mixed effects models, time series forecasting etc Strong programming ability, preferably in Python SQL and relational databases The company offer some great More ❯

designing, building, and scaling data platforms in production environments. Hands-on experience with big data technologies such as Airflow, DBT, Databricks, and data catalogue/observability tools (e.g. Monte Carlo, Atlan, Datahub). Knowledge of cloud infrastructure (AWS or GCP) - including services such as S3, RDS, EMR, ECS, IAM. Experience with DevOps tooling, particularly Terraform and More ❯

optimisation initiatives using advanced modelling techniques (e.g., AAD, Machine Learning). Candidate Profile Essential Skills & Experience: Strong programming skills in C++. Solid understanding of numerical methods such as Monte Carlo simulations and optimisation algorithms. Experience with: Distributed computing and inter-process communication Multi-threading programming Microsoft Office, VC++, VBA SQL databases (Access, Oracle) Web technologies (XML More ❯

optimisation initiatives using advanced modelling techniques (e.g., AAD, Machine Learning). Candidate Profile Essential Skills & Experience: Strong programming skills in C++. Solid understanding of numerical methods such as Monte Carlo simulations and optimisation algorithms. Experience with: Distributed computing and inter-process communication Multi-threading programming Microsoft Office, VC++, VBA SQL databases (Access, Oracle) Web technologies (XML More ❯