1 to 25 of 26 Permanent Analytical Modelling Jobs in Central London

work model – 3 days per week in the London office Role and Responsibilities Collaborate directly with trading and analytics teams to engineer, optimize, and automate front-office workflows and analytical models. Develop robust Python-based services and APIs using modern frameworks, microservice architectures, and best-practice design principles. Design and maintain tools that support market data ingestion, supply & demand More ❯

work model 3 days per week in the London office Role and Responsibilities Collaborate directly with trading and analytics teams to engineer, optimize, and automate front-office workflows and analytical models. Develop robust Python-based services and APIs using modern frameworks, microservice architectures, and best-practice design principles. Design and maintain tools that support market data ingestion, supply & demand More ❯

techniques such as data models, data flows, report specifications, and wireframes. Partner with the Data Engineering and BI teams to define and implement robust data pipelines, reporting solutions, and analytical models that support strategic decision-making and operational efficiency. Analyse data, including identifying sources, assessing data quality, defining lineage, and ensuring adherence to data governance standards. Translate complex business More ❯

techniques such as data models, data flows, report specifications, and wireframes. Partner with the Data Engineering and BI teams to define and implement robust data pipelines, reporting solutions, and analytical models that support strategic decision-making and operational efficiency. Analyse data, including identifying sources, assessing data quality, defining lineage, and ensuring adherence to data governance standards. Translate complex business More ❯

end analytics platform, delivering intuitive, high-performance tools that empower users with real-time insights and advanced visualization capabilities. Collaborate with commercial teams to engineer and optimize processes and analytical models. Build and maintain Python-based services and APIs using modern frameworks and best practices. Develop solutions for data modeling, market analysis, and position management. Design cloud-native tools More ❯

performance Develop, implement, and maintain robust ELT pipelines consuming data from internal systems and external partners Partner with business stakeholders and customers to unlock data insights and build impactful analytical models Investigate and resolve system defects, respond to production incidents, and conduct thorough code reviews Provide technical leadership by staying current with emerging technologies and mentoring team members Technical More ❯

performance Develop, implement, and maintain robust ELT pipelines consuming data from internal systems and external partners Partner with business stakeholders and customers to unlock data insights and build impactful analytical models Investigate and resolve system defects, respond to production incidents, and conduct thorough code reviews Provide technical leadership by staying current with emerging technologies and mentoring team members Technical More ❯

culture. Key Responsibilities: Architect, maintain, and optimise BW’s Microsoft Fabric ecosystem, ensuring scalable, efficient data workflows across the business. Design and deliver insightful, interactive Power BI dashboards and analytical models to drive decision-making. Translate complex business requirements into reliable, well-documented data structures and reporting frameworks. Implement data governance and quality controls, ensuring accuracy, consistency, and compliance … and data lakehouse concepts. Strong working knowledge of Databricks, including Delta Lake and notebooks. Strong interpersonal skills with the ability to influence and communicate complex data topics clearly. Excellent analytical, organisational, and problem-solving abilities. Experience leading or mentoring technical peers. Bonus Skills and Experience: Proficiency in Microsoft SQL Server, including stored procedures, triggers, and performance tuning. Familiarity with More ❯

driven culture. Key Responsibilities: Architect, maintain, and optimise BWs Microsoft Fabric ecosystem, ensuring scalable, efficient data workflows across the business. Design and deliver insightful, interactive Power BI dashboards and analytical models to drive decision-making. Translate complex business requirements into reliable, well-documented data structures and reporting frameworks. Implement data governance and quality controls, ensuring accuracy, consistency, and compliance … and data lakehouse concepts. Strong working knowledge of Databricks, including Delta Lake and notebooks. Strong interpersonal skills with the ability to influence and communicate complex data topics clearly. Excellent analytical, organisational, and problem-solving abilities. Experience leading or mentoring technical peers. Bonus Skills and Experience: Proficiency in Microsoft SQL Server, including stored procedures, triggers, and performance tuning. Familiarity with More ❯

Identify opportunities to improve performance, automate processes, and enhance data quality and reliability. Core Skills & Competencies Collaborative mindset: Works well with teams, communicates openly, and fosters a positive culture. Analytical thinking: Structured, detail-oriented, and curious; focused on accuracy and performance. Problem-solving: Able to trace issues across multiple systems and deliver elegant, lasting solutions. Communication: Able to explain … complex technical concepts clearly to technical and non-technical stakeholders. Required Skills & Experience Data warehousing: Understand differences between application databases and analytical warehouses; design models for both. Python: Strong expertise; C# experience is a plus. SQL: Comfortable with complex queries and query tuning on relational and analytical databases (e.g., PostgreSQL, ClickHouse). Containers: Experience building, running, and deploying More ❯

Identify opportunities to improve performance, automate processes, and enhance data quality and reliability. Core Skills & Competencies Collaborative mindset: Works well with teams, communicates openly, and fosters a positive culture. Analytical thinking: Structured, detail-oriented, and curious; focused on accuracy and performance. Problem-solving: Able to trace issues across multiple systems and deliver elegant, lasting solutions. Communication: Able to explain … complex technical concepts clearly to technical and non-technical stakeholders. Required Skills & Experience Data warehousing: Understand differences between application databases and analytical warehouses; design models for both. Python: Strong expertise; C# experience is a plus. SQL: Comfortable with complex queries and query tuning on relational and analytical databases (e.g., PostgreSQL, ClickHouse). Containers: Experience building, running, and deploying More ❯

the organization. Unlike the AI Architect, who evaluates individual AI capability, and the Data & AI Architect, who focuses on technical systems and platform maturity, this role centers on evaluating analytical workflows, modeling standards, experimentation culture, and applied business impact . This position is ideal for someone with a strong background in applied data science, model lifecycle design, and organizational … is conceived, executed, validated, and scaled. • Model Lifecycle Review: Assess practices across data preparation, feature engineering, model development, validation, monitoring, and iteration. • Tooling & Workflow Analysis: Review the ecosystem of analytical tools, frameworks, and environments used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). … as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to assess or design organizational processes for data science delivery and model management. • Excellent analytical and communication skills, with the ability to synthesize technical observations into actionable business recommendations. Preferred Skills • Experience designing or applying data science maturity models or capability frameworks. • Understanding of More ❯

the organization. Unlike the AI Architect, who evaluates individual AI capability, and the Data & AI Architect, who focuses on technical systems and platform maturity, this role centers on evaluating analytical workflows, modeling standards, experimentation culture, and applied business impact . This position is ideal for someone with a strong background in applied data science, model lifecycle design, and organizational … is conceived, executed, validated, and scaled. Model Lifecycle Review: Assess practices across data preparation, feature engineering, model development, validation, monitoring, and iteration. Tooling & Workflow Analysis: Review the ecosystem of analytical tools, frameworks, and environments used for data science, including reproducibility and collaboration readiness. Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). … as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Proven ability to assess or design organizational processes for data science delivery and model management. Excellent analytical and communication skills, with the ability to synthesize technical observations into actionable business recommendations. Preferred Skills Experience designing or applying data science maturity models or capability frameworks. Understanding of More ❯

the organization. Unlike the AI Architect, who evaluates individual AI capability, and the Data & AI Architect, who focuses on technical systems and platform maturity, this role centers on evaluating analytical workflows, modeling standards, experimentation culture, and applied business impact . This position is ideal for someone with a strong background in applied data science, model lifecycle design, and organizational … is conceived, executed, validated, and scaled. • Model Lifecycle Review: Assess practices across data preparation, feature engineering, model development, validation, monitoring, and iteration. • Tooling & Workflow Analysis: Review the ecosystem of analytical tools, frameworks, and environments used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). … as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to assess or design organizational processes for data science delivery and model management. • Excellent analytical and communication skills, with the ability to synthesize technical observations into actionable business recommendations. Preferred Skills • Experience designing or applying data science maturity models or capability frameworks. • Understanding of More ❯

the organization. Unlike the AI Architect, who evaluates individual AI capability, and the Data & AI Architect, who focuses on technical systems and platform maturity, this role centers on evaluating analytical workflows, modeling standards, experimentation culture, and applied business impact . This position is ideal for someone with a strong background in applied data science, model lifecycle design, and organizational … is conceived, executed, validated, and scaled. Model Lifecycle Review: Assess practices across data preparation, feature engineering, model development, validation, monitoring, and iteration. Tooling & Workflow Analysis: Review the ecosystem of analytical tools, frameworks, and environments used for data science, including reproducibility and collaboration readiness. Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). … as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Proven ability to assess or design organizational processes for data science delivery and model management. Excellent analytical and communication skills, with the ability to synthesize technical observations into actionable business recommendations. Preferred Skills Experience designing or applying data science maturity models or capability frameworks. Understanding of More ❯

permanent role, and the salary ranges between £60K - £70K + Bonus + Benefits. Hybrid working policy with 3 days in the office per week. Responsibilities include: - Design and deploy analytical models and dashboards to uncover insights, predict trends, and inform decision-making. - Provide data support to business transformation initiatives, ensuring alignment with strategic objectives and digital innovation goals. - Manage … experience - Hands-on experience with Google Cloud Platform tools including: BigQuery; Composer; Apache Airflow; Stream; Informatica; Vertex AI - Tableau dashboard development and reporting - Python programming for data analysis - Data modelling (warehouse, lakehouse, medallion architecture) - Understanding of financial and insurance data models - Insurance experience, ideally with knowledge of key industry metrics Please apply for immediate interview! CBSbutler is operating and More ❯

/London - £130K + Bonus & Benefits – FinTech Overview: An established global FinTech organisation is seeking a skilled Senior Analytics Engineer/Data Engineer to help define and manage its analytical data models and semantic layers. You will support the development of reliable, well-structured datasets that enable accurate reporting, improved data accessibility, and better decision-making across the business. … requirements into logical, scalable data models. Knowledge of cloud data platforms (e.g., Snowflake, Redshift, BigQuery). Strong communication and documentation skills. Structured, detail-oriented mindset. Desirable: Experience with semantic modelling tools (e.g., dbt SL, LookML). Familiarity with workflow orchestration and BI tooling. Version control experience (Git). Python for scripting. Offer Details: Type: Permanent Location: London/Hybrid More ❯

/London - 130K + Bonus & Benefits FinTech Overview: An established global FinTech organisation is seeking a skilled Senior Analytics Engineer/Data Engineer to help define and manage its analytical data models and semantic layers. You will support the development of reliable, well-structured datasets that enable accurate reporting, improved data accessibility, and better decision-making across the business. … requirements into logical, scalable data models. Knowledge of cloud data platforms (e.g., Snowflake, Redshift, BigQuery). Strong communication and documentation skills. Structured, detail-oriented mindset. Desirable: Experience with semantic modelling tools (e.g., dbt SL, LookML). Familiarity with workflow orchestration and BI tooling. Version control experience (Git). Python for scripting. Offer Details: Type: Permanent Location: London/Hybrid More ❯

analytics and applied data science - using data to understand behaviour, identify opportunities, and guide strategic decisions across marketing, product, and personalising customer experience. Key Responsibilities Translate business challenges into analytical questions and deliver data-led insights that drive customer growth and retention. Analyse customer behaviour, lifecycle patterns, and engagement to uncover opportunities for product and marketing optimisation. Develop and … maintain advanced analytical models to forecast customer outcomes and measure impact. Present clear, data-driven recommendations to senior stakeholders, influencing strategy and decision-making. Work closely with Data Engineering and BI teams to ensure data quality, accessibility, and scalability across the organisation. What We’re Looking For Strong analytical foundation with experience applying statistics and data science in More ❯

and interpretation of model outputs. They should be up to date with the latest trends and developments in marketing measurement. They should be able to interpret complex data and analytical insights, including those derived from MMM, and present them in a clear, concise, and actionable manner to clients, translating technical findings into strategic business recommendations. The Senior Client Success … processes for work delivery and client satisfaction, specifically for projects involving advanced analytics and MMM. Deliver high-quality client materials in line with strategic objectives, ensuring clear articulation of analytical insights and MMM recommendations. Contribute to collaborative team learning and knowledge sharing to strengthen capabilities, particularly in areas of marketing effectiveness measurement and MMM best practices. Deliver in specific … and management as defined by client leadership, including leading discussions on MMM results and their implications. Support with client growth initiatives and new business pitches, showcasing Gain Theory's analytical capabilities and MMM expertise. Cross-collaboration with analytics, data, and ops team members to ensure a well-functioning squad with high levels of satisfaction, acting as a key liaison More ❯

Science, Artificial Intelligence, Mathematics, Statistics or related fields. Strong communication skills, with the ability to work effectively in a fast-paced, collaborative environment. Ability to translate business problems into analytical solutions using advanced modelling techniques. Please note: ** This role does not offer visa sponsorship More ❯

Science, Artificial Intelligence, Mathematics, Statistics or related fields. Strong communication skills, with the ability to work effectively in a fast-paced, collaborative environment. Ability to translate business problems into analytical solutions using advanced modelling techniques. Please note: ** This role does not offer visa sponsorship More ❯

Science, Artificial Intelligence, Mathematics, Statistics or related fields. Strong communication skills, with the ability to work effectively in a fast-paced, collaborative environment. Ability to translate business problems into analytical solutions using advanced modelling techniques. Please note: ** This role does not offer visa sponsorship More ❯

Science, Artificial Intelligence, Mathematics, Statistics or related fields. Strong communication skills, with the ability to work effectively in a fast-paced, collaborative environment. Ability to translate business problems into analytical solutions using advanced modelling techniques. Please note: ** This role does not offer visa sponsorship More ❯

years of equity research experience, either buy-side or sell-side Strong expertise and passion for the Software sector CFA qualified or working towards qualification Excellent academic record and analytical rigour Strong financial modelling skills Openness to healthy debate, willingness to challenge the consensus and have courage of your convictions Team player who enjoys working in a collaborative More ❯