22 of 22 Propensity Modelling Jobs in the UK

Data Scientist Welwyn Garden City, Hertfordshire or Slough, Berkshire | Hybrid (2 Days Office) | Python | SQL | PySpark | Azure | Databricks | Machine Learning | Statistics | Time Series Forecasting | Propensity Models Role: Senior Data Scientist, Lead Data Scientist, ML Scientist, AI Data Scientist, Statistical Data Scientist, Predictive Analytics Key Skills: Senior Data Scientist, Data … Scientist, Machine Learning, Artificial Intelligence, Predictive Analytics, Statistical Modelling, Python, SQL, PySpark, Azure, Databricks, MLflow, GitHub Actions, CI/CD, Time Series Forecasting, Propensity Modelling, Feature Engineering, Data Engineering, Azure Machine Learning, Azure Data Platform, Experiment Design, A/B Testing, Hypothesis Testing, Predictive Modelling, Customer ...

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 ...

causal inference to distinguish genuine impact from correlation? Have you applied propensity methods or counterfactual modelling to customer or product data? Would you like to help move an established Data Science team from prediction into causality? A major global consumer technology business is hiring a Data Scientist into … what would have happened if that action had not occurred? Responsibilities • Build causal solutions to quantify the incremental value of customer behaviours • Apply propensity scoring, propensity score matching, Double Machine Learning and counterfactual methods • Move existing customer value capabilities from prediction towards causality and incrementality • Build and productionise ...

track record of delivering production-ready Machine Learning solutions.* You have experience across customer, marketing or commercial Data Science, including recommendation systems, experimentation, pricing, propensity modelling, uplift modelling or similar use cases.* You're confident communicating complex technical concepts to both technical and non-technical audiences, helping ...

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 ...

develop a team of Data Scientists while defining best practices across the function Design and deploy machine learning models across forecasting, customer segmentation, and propensity modelling Own end-to-end model development including feature engineering, validation, deployment, and monitoring Partner with Engineering and Product teams to build scalable ...

Data Scientist Welwyn Garden City, Hertfordshire or Slough, Berkshire Hybrid (2 Days Office) Python SQL PySpark Azure Databricks Machine Learning Statistics Time Series Forecasting Propensity Models Role: Senior Data Scientist, Lead Data Scientist, ML Scientist, AI Data Scientist, Statistical Data Scientist, Predictive Analytics Key Skills: Senior Data Scientist, Data ...

solved at both a tactical and strategic level. Experience delivering marketing analytics e.g., Marketing Mix Modeling , geo experiments, meta-analysis, audience segmentation and propensity modeling . Understanding of Bayesian approaches and modeling frameworks. Proven ability to generate practical solutions for marketing analytics problems and use results to drive business ...

solved at both a tactical and strategic level. Experience delivering marketing analytics e.g., Marketing Mix Modeling , geo experiments, meta-analysis, audience segmentation and propensity modeling . Understanding of Bayesian approaches and modeling frameworks. Proven ability to generate practical solutions for marketing analytics problems and use results to drive business ...

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 ...

Annalect team supports advanced use cases, helping clients customize their internal results to the tool, and apply advanced methods to enable better planning. Propensity modelling and activation – building and deploying algorithms that ensrue clients can reach their KPIs and targets in automated, streamlined way. Applied AI solutions – build ...

logic. Translate commercial conditions (margin, fee bands, seller activation) into schema logic. Contribution & Incrementality Optimisation Optimise towards incremental GMV and contribution, not ROAS. Use propensity modelling outputs, EXTA parameters, decile segmentation, and SKU-level economics to shape structure and bids. Lead the Daily Trading Room: identify opportunities, isolate … PMax, Shopping Profit frameworks, and revenue tracking systems. Ensure structure and tracking changes are documented, measurable, and repeatable. Partner with Data Science to operationalise propensity segmentation. Own end‐to‐end conversion tracking integrity, including server‐side conversions API, GTM audits, feed attribution, and ongoing monitoring of tracking capture rates ...

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 ...

best practiceDesirable: experience in subscription or recurring revenue models, partnerships/affiliate or co-registration models, portfolio/multi-brand environments, and exposure to propensity modellingBenefits... (Your benefits at Hearst UK are more than just extras—they are tools to help you thrive in every part of life.)Hearst ...

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 ...

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 ...

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 ...

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 ...

records are the same company: domain and firmographic matching, confidence scoring, and the merge/dedupe pipelines that keep Salesforce clean at scale. Modelling account hierarchy. Designing the organisation spine that links accounts to their parent, top operating parent and ultimate corporate parent. Building account sourcing pipelines. Turning market … havesExperience with GTM data vendors and tooling — ZoomInfo, Apollo, Clearbit, Clay, Crossbeam, Marketo, Census/Fivetran, Gong. Experience with territory design, account scoring, propensity models or ICP definition. Exposure to privacy and compliance considerations around contact data (GDPR, CCPA, consent management).#LI-HybridAt Fin, we want to give people ...