1 to 25 of 35 Propensity Modelling Jobs in the UK

transformation towards a subscription-led model, with Data Science becoming a critical part of future growth. What you'll be working on Subscription propensity modelling Churn prediction and retention analytics Customer segmentation and personalisation Dynamic pricing and offer optimisation Uplift modelling and causal inference Experimentation frameworks … theory Experience working with large-scale customer datasets Background in subscription, consumer, media, gaming, e-commerce, fintech or similar environments Experience with recommendation systems, propensity modelling, retention, personalisation or monetisation challenges would be particularly valuable. Founding hire into a growing Data Science capability Huge influence over future direction ...

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 ...

Role: Data Science Associate Manager (Customer)Team: Song AI & Data – AI & Modelling Craft, UK&ILocation: London/ManchesterCareer Level: Associate Manager (L8)We AreAccenture Song accelerates growth and value for our clients through sustained customer relevance. Our capabilities span ideation to execution: growth, product and experience design; technology … analytics, performance optimisation, and AI (including generative AI and agentic AI) transformation. You will join the Song AI & Data UK practice, within the AI & Modelling Craft: a community of data scientists, AI engineers, modellers and solution architects focused on applying AI, machine learning and advanced analytics to solve customer ...

doing Lead the design, development, and delivery of analytical data products that support insight‐led business decisions. Examples may include customer value models, propensity models, performance measurement frameworks, forecasting solutions and self‐service insight products. Partner with Consumer Insights colleagues to combine behavioural, transactional and attitudinal research data into … Experience as a critical thought partner in defining analytical solutions, challenging assumptions constructively. Experience applying customer analytics techniques such as customer lifetime value modelling, segmentation, cohort analysis, propensity modelling or retention analysis. Proven experience in stakeholder‐facing analytics roles, with a track record of influencing decisions through ...

role if you bring: Professional experience in data analysis, business intelligence, analytics engineering or a closely related role. Strong experience of data preparation, cleansing, modelling and quality assurance. Experience using SQL and visualisation tools such as Power BI, Microsoft Fabric or equivalent platforms. Experience working with CRM, customer, commercial … Microsoft technologies. Familiarity with OpenClaw, Hermes or similar agent platforms. Track record of measuring AI, automation or digital‐product performance. Knowledge of predictive analytics, propensity modelling, segmentation or recommendation systems. Understanding of marketing attribution, customer journey analytics or revenue analysis. Ability to design trusted data products or reusable ...

quantitative field Preferred: experience taking initial machine learning models from exploratory notebooks to automated production pipelines Preferred: experience in customer behavior and propensity modeling, forecasting, optimization, or causal inference Core Competencies Demonstrates expertise in Data Science and Machine Learning Engineering, with a strong focus on developing production-ready models ...

driven analytics that support strategic decision-making across the business. To succeed, you'll bring significant experience in commercial intelligence or analytics, strong data modelling expertise, and the ability to influence senior stakeholders through insight-led recommendations. ResponsibilitiesBuild and evolve BSI's enterprise commercial intelligence framework Develop commercial data … models covering pipeline, forecasting, segmentation and account health Lead the development of AI and machine learning capabilities to improve forecasting, propensity modelling and churn detection Create integrated dashboards and reporting that provide visibility across the commercial lifecycle Establish governance standards for commercial data quality, consistency and usage Identify ...

CDPs (Salesforce Data Cloud, Adobe Experience Platform, Treasure Data, mParticle), MDM, CRM, and data warehousing Familiar with analytical approaches used in customer strategy: segmentation, propensity modelling, next‐best‐action, attribution, and customer journey analytics — ability to interpret and apply, not necessarily build Knowledge of cloud data platforms (Azure ...

science, partnering with product managers, engineers and designers to embed data-driven decision making across the Engagement & Discovery squad. You will build churn and propensity models, perform deep analyses, and explore lifecycle drivers to guide acquisition, engagement and retention at scale. #J-18808-Ljbffr ...

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 ...

complex querying, data transformation and analysis. Dashboard development and digital performance measurement. Significant experience designing and building advanced Power BI solutions, including data modelling and DAX. Experience working within marketing analytics, digital analytics, business intelligence or related analytical environments. Strong understanding of marketing performance measurement, attribution and customer journey … data platforms such as Azure, AWS, GCP, Snowflake or BigQuery. Familiarity with CRM, CDP, marketing automation and paid media platforms. Experience developing predictive analytics, propensity models or automated insight solutions. Responsible Artificial Intelligence usage. What We Will Offer You Recognised and rewarded for a job well done, we have ...

optimisation. Perform exploratory data analysis to understand product usage, engagement, and conversion behaviour. Develop predictive models, including churn prediction, engagement scoring, demand forecasting, and propensity modelling. Build customer segments and behavioural cohorts to support product, marketing, and customer success initiatives. Translate business questions into structured analytical approaches and actionable … similar analytics professional. Advanced SQL skills and experience working with cloud-based data warehouse environments. Strong Python or R capabilities for data analysis, statistical modelling, and machine learning. Experience building predictive models and applying analytical techniques to solve business problems. Understanding of customer journey analysis, funnel optimisation, retention analysis ...

role moves beyond traditional reporting to use data to understand audiences, inform fundraising decisions, and generate actionable insight. You'll develop audience profiling, segmentation, propensity modelling and lifetime value analyses, while ensuring current reporting remains strong. #J-18808-Ljbffr ...

models in an organization from exploratory notebooks to reliable, automated production pipelines. Advanced Business ML (Experience in 1-2 of the following): Customer Behavior & Propensity Modeling: Building predictive models for churn, propensity-to-buy, lead scoring, or lifetime value (LTV) to directly drive targeted marketing and product interventions. ...

models in an organization from exploratory notebooks to reliable, automated production pipelines. Advanced Business ML (Experience in 1-2 of the following): Customer Behavior & Propensity Modeling: Building predictive models for churn, propensity-to-buy, lead scoring, or lifetime value (LTV) to directly drive targeted marketing and product interventions. ...

professional. Strong analytical and problem-solving skills, including the ability to create clarity from ambiguous business questions. Advanced Python skills for data analysis and modelling, together with strong SQL capability. Practical experience applying statistical and data-science techniques to business problems, including several of forecasting, regression, classification, segmentation … propensity modelling. Sound understanding of statistical concepts, model evaluation, uncertainty, bias and the limitations of analytical approaches. Experience working with large or complex datasets and performing data discovery, validation and exploratory analysis. Excellent requirements-gathering, stakeholder-management and project-planning skills. Excellent written communication, with experience producing analytical papers ...

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 ...

subscribers - across viewing behaviour, curation, pricing and lifecycle - and turn what you find into action. Build models that inform decisions. Develop churn and propensity models, LTV estimates and behavioural segmentations that sharpen how we target, retain and delight subscribers. Put AI to work. Use tools like Claude Code … accelerate analysis and modelling, and help the team do the same. What you'll bring 3-5 years of experience in product analytics, product data science, or a similar role, ideally in a consumer subscription or digital product business. A strong grounding in data science methods - statistics, experimentation ...

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

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

earliest data hires. You'll work closely with the Head of Credit, Credit Risk Manager and CTO to build our modelling capability from the ground up — from scorecard development and underwriting automation to portfolio analytics and early warning systems as well as Customer Lifetime Values. This … things, building the infrastructure, and helping recruit the team around you as we grow. Key Responsibilities Build credit risk models - application scorecards, behavioural models, propensity models - across our SME lending products Create portfolio monitoring dashboards, MI packs, and early warning indicators for the credit and leadership teams Work with ...

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 ...