13 of 13 Propensity Modelling Jobs in the UK

function while remaining closely involved in the most commercially important analytical work. You will: Lead, mentor, and develop a team of Data Scientists. Establish modelling standards, validation frameworks, and best practices. Deliver forecasting, customer segmentation, propensity modelling, and machine learning solutions. Take ownership of complex analytical challenges … team environment. A consulting, professional services, or highly client-facing background. This is essential. Strong Python and SQL expertise. Experience delivering forecasting, segmentation, propensity modelling, and predictive analytics projects. Exposure to production machine learning environments and ML Ops practices. Excellent communication skills with the ability to influence both ...

data to understand audiences, inform fundraising decisions and generate genuinely actionable insight. You'll help develop areas such as audience profiling and segmentation, propensity modelling and lifetime value analysis, while ensuring existing reporting and data selections continue to be delivered effectively. The role would suit an experienced Insight … analysts, providing direction and helping develop the organisation's insight capability Move the function beyond reporting into more advanced analysis, including segmentation, audience profiling, propensity modelling and lifetime value Use tools such as SQL and Power BI to turn complex data into meaningful, actionable insight Work closely with ...

level Data Scientist role focused on developing and deploying customer-focused machine learning models. Projects include: Customer segmentation Customer Lifetime Value (CLTV) modelling Demand forecasting Propensity modelling Targeted promotions and campaign optimisation Data Science initiatives linked to a major new loyalty programme The team are still early ...

scalable, reusable, market-adaptable and aligned with enterprise data architecture. Partner with engineering and architecture teams to ensure the right ingestion, harmonisation, modelling, semantic layer and visualisation approaches are applied. Ensure consumer data products can support both descriptive and advanced analytics use cases, including segmentation, propensity modelling ...

broken, you fix it. What You Will Do Decisioning & Data Science Design and implement NBA/NBO decisioning frameworks — eligibility rules, suppression logic, propensity score integration, offer prioritisation, and arbitration Operationalise propensity models, uplift models, CLV scores, and churn predictions into live decisioning frameworks Use value-based decisioning … decisioning solution — Pega CDH, Salesforce Marketing Cloud, Adobe Target/AEM/Campaign, Braze, Iterable, or purpose-built solutions Strong working knowledge of predictive modelling for decisioning: propensity, churn, CLV, uplift, and incrementality Experience designing statistically valid champion/challenger and multivariant tests and holdout methodologies Ability ...

broken, you fix it. What You Will Do Decisioning & Data Science Design and implement NBA/NBO decisioning frameworks — eligibility rules, suppression logic, propensity score integration, offer prioritisation, and arbitration Operationalise propensity models, uplift models, CLV scores, and churn predictions into live decisioning frameworks Use value-based decisioning … decisioning solution — Pega CDH, Salesforce Marketing Cloud, Adobe Target/AEM/Campaign, Braze, Iterable, or purpose-built solutions Strong working knowledge of predictive modelling for decisioning: propensity, churn, CLV, uplift, and incrementality Experience designing statistically valid champion/challenger and multivariant tests and holdout methodologies Ability ...

When something is broken, you fix it. What You Will DoDecisioning & Data ScienceDesign and implement NBA/NBO decisioning frameworks — eligibility rules, suppression logic, propensity score integration, offer prioritisation, and arbitrationOperationalise propensity models, uplift models, CLV scores, and churn predictions into live decisioning frameworksUse value-based decisioning logic … decisioning solution — Pega CDH, Salesforce Marketing Cloud, Adobe Target/AEM/Campaign, Braze, Iterable, or purpose-built solutionsStrong working knowledge of predictive modelling for decisioning: propensity, churn, CLV, uplift, and incrementalityExperience designing statistically valid champion/challenger and multivariant tests and holdout methodologiesAbility to critically evaluate model ...

ground up. This is a genuinely hands-on role where you'll have ownership of the full data science lifecycle - from defining the modelling approach and building predictive models through to creating scalable, repeatable and production-ready solutions. The initial focus will be on customer churn and complaint propensity , alongside forecasting and other predictive modelling opportunities. You'll be responsible for building the models, documenting the methodology and establishing the overall approach that can be embedded and scaled across the business. What we're looking for We're particularly interested in Data Scientists who have built churn ...

range of credit models in the business and take on a challenging role which will give you excellent exposure and experience in the credit modelling space. Day to Day the Lead Data Scientist will: Manage and Run the Data Science Team Build a new Data Warehouse Build the Data … Environment Build out a new set of credit model Work across the current range of credit models within the business, including scorecards, propensity models, and IFRS9 models Develop challenger models to improve and enhance the modelling suite Monitor and report on these models, taking oversight across the modelling ...

marketing, with at least 2–3 years owning a channel or function end-to-end* Hands-on with data: you personally build response/propensity models and write the SQL/Python to source, clean and join the data behind them* Track record scaling a measurable acquisition or retention … attribution* A commercial communicator who can earn the trust of finance, data, product and engineering* Demonstrable use of AI in your workflow (analysis, creative, modelling, automation)**Desirable:*** Experience in financial services, regulated or other consumer categories where offers and eligibility matter* Experience standing up a data pipeline or enrichment ...

range of credit models in the business and take on a challenging role which will give you excellent exposure and experience in the credit modelling space. Day to Day the Lead Data Scientist will: Build a new Data Warehouse Build out a new set of credit model Work across … current range of credit models within the business, including scorecards, propensity models, and IFRS9 models Develop challenger models to improve and enhance the modelling suite Monitor and report on these models, taking oversight across the modelling processLead Data Scientists should have: 5 years of Data Science experience ...

EMEA ENT CSC. The CSC works at scale across a broad portfolio of Enterprise customers, using AI-first sales motions: leveraging data signals and propensity models to identify expansion opportunities and convert them into revenue — combining strategic depth with velocity and operating leverage. The mission is to help customers … wave of adoption. The CSC works at scale across a broad portfolio of Enterprise customers, using AI-first sales motions: leveraging data signals and propensity models to identify expansion opportunities and convert them into revenue — combining strategic depth with velocity and operating leverage. The mission is to help customers ...

thrive in a high-ambiguity, high-velocity environment and shape direction without waiting for permission- Data-driven approach to prioritization using pipeline data, propensity signals, and market intelligence to focus effort where it matters most- Experience in enterprise technology sales, solutions architecture, or technical business development with a focus … customer roundtables, GenAI workload assessments, use-case workshops, developer engagement, and regional campaigns that create demand and accelerate adoption.- Thought Leadership : Create packaged deliverables (propensity models, use-case frameworks) and drive enablement that raises the bar across the EMEA field.- Be the voice of EMEA customers to Product: synthesise ...