8 of 8 Regression Analysis Jobs in London

value from complex financial data, partnering closely with Finance Managers and senior stakeholders to deliver advanced analytical projects from end to end. You'll apply statistical techniques such as regression analysis, time series modelling, and hypothesis testing to uncover trends, forecast outcomes, and solve business challenges. Your insights will drive strategic decisions, and you'll be responsible for … environment. Essential Criteria Educational degree in Mathematics, Statistics, Data Science, or a related analytical field is desirable Experience applying statistical techniques and modelling in a commercial setting (such as regression analysis, time series forecasting and hypothesis testing). Exposure to machine learning methods, including supervised and unsupervised learning, and model evaluation Experience in SQL and Python for advance More ❯

has not previously been obtainable. The Role: Data Cleaning and Preparation: Collect, clean, and prepare large media datasets from various sources (CRM, ad servers, audience panels) for analysis. Statistical Analysis: Utilise econometric techniques like regression analysis, time series modelling, and panel data analysis to identify relationships between media spend and business outcomes. Model Validation and Interpretation … a clear and concise manner. Campaign Optimisation: Provide data-driven insights to inform media buying strategies, including channel allocation, budget optimisation, and creative testing. Advanced Analytics: Explore new data analysis techniques like machine learning to enhance model accuracy and uncover deeper insights. Your Experience and Skills: Data Science: Proficient in programming languages like Python, R, and SQL including data … manipulation, data imputation, statistical modelling, and visualisation libraries. Econometrics Background Useful: Expertise in statistical methods like linear regression, generalised linear models, panel data analysis, and time series forecasting. Media Industry Knowledge: Understanding of media landscape, ad formats, audience measurement, and industry KPIs. Communication Skills: Ability to clearly communicate complex statistical concepts and insights to non-technical stakeholders. Business More ❯

has not previously been obtainable. The Role: Data Cleaning and Preparation: Collect, clean, and prepare large media datasets from various sources (CRM, ad servers, audience panels) for analysis. Statistical Analysis: Utilise econometric techniques like regression analysis, time series modelling, and panel data analysis to identify relationships between media spend and business outcomes. Model Validation and Interpretation … a clear and concise manner. Campaign Optimisation: Provide data-driven insights to inform media buying strategies, including channel allocation, budget optimisation, and creative testing. Advanced Analytics: Explore new data analysis techniques like machine learning to enhance model accuracy and uncover deeper insights. Your Experience and Skills: Data Science:Proficient in programming languages like Python, R, and SQL including data … manipulation, data imputation, statistical modelling, and visualisation libraries. Econometrics Background Useful: Expertise in statistical methods like linear regression, generalised linear models, panel data analysis, and time series forecasting. Media Industry Knowledge: Understanding of media landscape, ad formats, audience measurement, and industry KPIs. Communication Skills: Ability to clearly communicate complex statistical concepts and insights to non-technical stakeholders. Business More ❯

has not previously been obtainable. The Role: Data Cleaning and Preparation: Collect, clean, and prepare large media datasets from various sources (CRM, ad servers, audience panels) for analysis. Statistical Analysis: Utilise econometric techniques like regression analysis, time series modelling, and panel data analysis to identify relationships between media spend and business outcomes. Model Validation and Interpretation … a clear and concise manner. Campaign Optimisation: Provide data-driven insights to inform media buying strategies, including channel allocation, budget optimisation, and creative testing. Advanced Analytics: Explore new data analysis techniques like machine learning to enhance model accuracy and uncover deeper insights. Your Experience and Skills: Data Science:Proficient in programming languages like Python, R, and SQL including data … manipulation, data imputation, statistical modelling, and visualisation libraries. Econometrics Background Useful: Expertise in statistical methods like linear regression, generalised linear models, panel data analysis, and time series forecasting. Media Industry Knowledge: Understanding of media landscape, ad formats, audience measurement, and industry KPIs. Communication Skills: Ability to clearly communicate complex statistical concepts and insights to non-technical stakeholders. Business More ❯

has not previously been obtainable. The Role: Data Cleaning and Preparation: Collect, clean, and prepare large media datasets from various sources (CRM, ad servers, audience panels) for analysis. Statistical Analysis: Utilise econometric techniques like regression analysis, time series modelling, and panel data analysis to identify relationships between media spend and business outcomes. Model Validation and Interpretation … a clear and concise manner. Campaign Optimisation: Provide data-driven insights to inform media buying strategies, including channel allocation, budget optimisation, and creative testing. Advanced Analytics: Explore new data analysis techniques like machine learning to enhance model accuracy and uncover deeper insights. Your Experience and Skills: Data Science:Proficient in programming languages like Python, R, and SQL including data … manipulation, data imputation, statistical modelling, and visualisation libraries. Econometrics Background Useful: Expertise in statistical methods like linear regression, generalised linear models, panel data analysis, and time series forecasting. Media Industry Knowledge: Understanding of media landscape, ad formats, audience measurement, and industry KPIs. Communication Skills: Ability to clearly communicate complex statistical concepts and insights to non-technical stakeholders. Business More ❯

or similar. Develop and maintain reports to support business performance monitoring. Work with stakeholders to define key performance indicators (KPIs) and reporting requirements. Use statistical tools and techniques (e.g., regression analysis, hypothesis testing) to support data-driven decision-making. Collaborate with data engineers and IT to ensure data integrity and optimize data pipelines. Present findings to stakeholders in More ❯

home data to measure campaign effectiveness at impression and outcome level. Lead on brand lift measurement, showing how advertising works and refining the signals that prove campaign impact. Apply regression analysis, MMM techniques and work with AI/LLMs where relevant. Collaborate closely with engineering and product teams to integrate data from multiple systems. Translate insights into clear … technical stakeholders, focusing on outcome metrics and campaign improvement. You Experienced Data Scientist with a background in fraud, methodology, and campaign/brand measurement. Strong technical skills across Python, regression modelling and MMM. Confident working with large datasets and combining app, web and device-level data. Able to operate at outcome level, translating complex data into clear commercial recommendations. More ❯

Object, SQL, NOSQL) • Authentication, Authorisation, Identity Platforms • Information Security, Privacy and Regulatory Compliance • Performance Tuning, Hardening and Troubleshooting • Problem Solving Skills to Methodically Find Faults and perform Root Cause Analysis • Able to evaluate multiple courses of action, achieving goals by non-standard means if necessary • System Regression • Protocol Analysis • Load Testing • Availability and Resilience Optimisation • Lockdowns and More ❯