1 to 25 of 34 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 ❯

technologies. Profile Strong programming experience in Python, C++, or C#; knowledge of NumPy, Pandas, and QuantLib advantageous. Solid understanding of mathematics, statistics, and numerical methods - including stochastic calculus, Monte Carlo simulation, and optimisation. Familiarity with derivatives pricing, risk metrics, and financial instruments across asset classes. Experience building low-latency systems and optimising performance for computational workloads. 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯