351 to 375 of 458 Predictive Modelling Jobs in the UK

This is a very interesting project focused on pricing optimisation for insurance companies, using an ensemble of predictive models. The tech stack includes: pandas, numpy, PyTorch, SHAP, and scikit-learn. We are looking for candidates with experience in building predictive models for time series, strong attention to detail … support hypothesis testing and data-driven decisions during EDA Implement data preparation and feature engineering pipelines for the models Plan and implement algorithms for predictive modeling. Provide continuous improvement of models in production Lead the ML-driven python coding for end-to-end model deliveries, support our ML-related ...

critical business areas. Operating within Agile cross-functional squads, they lead teams to scope, design, build, deploy and maintain scalable, production-ready solutions - including predictive models, optimisation engines, and decision-support tools - that integrate seamlessly with business processes and technical infrastructure. The Principal Data Scientist delivers in line with … manipulates complex and large raw data to ensure high-quality inputs for models Designs, builds and trains data science products such as business models, predictive analytics tools, recommender systems, natural language processing, anomaly detection, forecasts, optimisation models and decision support systems Works with Digital teams to productionise models ...

Data Architects to implement target‐state data models and modern data engineering principles. Partner with data scientists and analysts to operationalise advanced analytics and predictive models. Manage integrations with insurer portals and external data providers, ensuring high‐quality, timely and secure data flows. Support the organisation's ambition … data platforms. Comfortable working in regulated data environments with sensitive personal and litigation data. Excellent stakeholder management and communication skills. Desirable Experience Exposure to predictive analytics, machine learning operationalisation or AI platforms. Experience working with Dynamics CRM, case management platforms such as VisualFiles, and finance systems such as Elite ...

Data Architects to implement target-state data models and modern data engineering principles. Partner with data scientists and analysts to operationalise advanced analytics and predictive models. Manage integrations with insurer portals and external data providers, ensuring high-quality, timely and secure data flows. Support the organisation's ambition … data platforms. Comfortable working in regulated data environments with sensitive personal and litigation data. Excellent stakeholder management and communication skills. Desirable Experience Exposure to predictive analytics, machine learning operationalisation or AI platforms. Experience working with Dynamics CRM, case management platforms such as VisualFiles, and finance systems such as Elite ...

process and change within the organization. Data-Driven Action Requirements: Leverage large-scale marketing performance data using advanced analytics and data science techniques (e.g., predictive modeling, segmentation, regression analysis) to identify actionable insights. Drive digital, web, demand and pipeline analytics. Build and refine predictive and diagnostic models ...

feature engineering, model development, and deployment. Working with large and complex datasets, you'll use Python, PySpark, SQL, and Azure Databricks to develop robust predictive models and analytical solutions. Just as importantly, you'll be able to explain your findings in a clear and engaging way, helping stakeholders understand … work on highly visible projects that directly shape the experience of millions of customers. Key responsibilities Develop and deploy machine learning and predictive analytics solutions that address key business challenges and deliver measurable commercial outcomes Explore, profile, and analyse large and complex datasets to identify trends, opportunities, and features ...

drive innovation and challenge conventional approaches. The Role You will: Develop and deploy machine learning models that support pricing and risk management strategies. Build predictive models focused on claims outcomes, fraud detection, and key business performance metrics. Create and maintain analytical tools used to manage and optimise risk portfolios. … Identify, assess, and utilise new data sources to improve model performance and business outcomes. Engineer new predictive features that can be incorporated into pricing algorithms. Take ownership of projects across the full machine learning lifecycle, from exploratory analysis through to deployment and monitoring. Collaborate with Data Scientists, Data Engineers ...

engineering ecosystem to deliver AI components that are robust, scalable, and deployed into live environments. Key Responsibilities Machine learning engineering Design, train and optimise predictive models using advanced architectures such as gradient boosted trees, temporal models and embedding based models. Build robust training, evaluation and monitoring pipelines to ensure … performance optimisation. Productionise models so they run reliably and efficiently at scale in client environments. Data engineering Own schema aware data flows for modelling and cohorts; validate, transform and version datasets used in training and inference. Manage and evolve database schemas; optimise SQL, indexing and partitioning for large training ...

deliver our scientific vision for next-gen drug discovery services. You will lead across biology, chemistry, and computational sciences, driving AI-enabled design, predictive modelling, and translational biology, while partnering with clients to advance programs from concept toward clinic in a scale-driven environment. #J-18808-Ljbffr ...

shaping data-driven digital experiences across our direct-to-consumer products in London. You will own the Product Analytics strategy, roadmap and delivery, building predictive models and implementing experimentation to optimise customer journeys, engagement and retention. Lead a high-performing team, partner with Product, Design and Engineering, and embed ...

business leaders to translate insights into actionable strategies, develop executive-ready presentations, and collaborate with cross-functional teams to advance self-service analytics and predictive modeling. #J-18808-Ljbffr ...

Turbine is building Virtual Assays—AI‐powered predictive models that can run biological experiments in silico. We seek an experienced VP of AI to lead our AI and computational biology efforts, scaling our platform and mentoring a world‐class team. You will define strategy, ensure reproducible AI capabilities ...

lead pricing across insurance lines, shaping pricing strategy with advanced analytics and strong stakeholder engagement. You will coach teammates, champion best practice, and develop predictive models (GLM, GBM, LTV) using WTW Radar and Emblem, driving value for customers and the business. In a fast-paced environment you’ll manage ...

analytics into workforce decisions. You will drive data-driven, executive-ready insights at scale, collaborating with cross-functional teams to develop self-service capabilities, predictive models, and impactful narratives that shape talent strategy globally. #J-18808-Ljbffr ...

rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together! You will join the Predictive Intelligence engineering team within Anaplan, building the backend services that power the ML Engine behind the Syrup platform and Anaplan’s forecasting solutions. The team … responsible for the production execution of forecasting and predictive models, the MLOps infrastructure supporting our data scientists, and the data processing services that deliver insights to enterprise customers. This role reports to the Director of Engineering for Predictive Intelligence and works closely with data scientists, ML engineers ...

deploying and monitoring models in production. We are looking for someone with 3-5 years of commercial data science experience, combining strong analytical and modelling skills with practical experience of taking models beyond experimentation and into production. Experience developing scoring or predictive models, particularly using FMCG, retail … consumer behavioural data, would be a significant advantage. Key Responsibilities Develop, test and validate statistical, machine learning and predictive models to solve real-world business problems. Take ownership of solutions from initial exploration and prototyping through to deployment and ongoing monitoring. Work with engineering and data teams to deploy ...

maximise business value. Define requirements for improving data quality, accuracy and reliability across reporting and decision-support tools. Work with Data Science teams where predictive models and advanced analytics form part of a data product. Support the continuous improvement of business intelligence and data product capabilities through innovation … business strategy and how data supports organisational objectives. Awareness of systems architecture and core business systems. Understanding of data science principles and how predictive analytics can enhance business decision-making. Excellent communication and stakeholder management skills, with the ability to influence and challenge constructively. Strong analytical, modelling ...

Architect AI Architect Excited to uncover insights from complex data and turn them into impactful business decisions? Do you enjoy building predictive models, experimenting with advanced analytics, and solving real-world challenges with data? About the team: LexisNexis Intellectual Property Solutions (LNIP) is the global leader in patent intelligence … architecture vision for Protégé in PatentSight+, ensuring technical decisions are coherent, future‐proof, and aligned with product strategy. Evaluate and recommend AI technologies, modelling approaches, and platform components. Stay up to date with advances in agentic AI and domain‐specific AI research. Translate emerging capabilities into practical architectural recommendations. ...

optimize GPU utilization, workload scheduling, and system efficiency in real time. You will design experiments, analyze large-scale system telemetry data, and build predictive and optimization solutions that are tightly integrated into production workflows. This role blends hands‐on deployment with analytical rigor, turning complex infrastructure data into measurable … with distributed data systems (Spark, Ray, Dask, or similar) Proficiency in SQL and working with large-scale structured datasets Experience building, deploying, and maintaining predictive models in production environments Strong understanding of optimization techniques (linear programming, convex optimization, stochastic optimization, or reinforcement learning) Experience working with time‐series data ...

know everything from day one, but you should be able to demonstrate the following: Strong knowledge and experience of using statistical methods, predictive models, and machine learning techniques to achieve business objectives. This should include (but is not limited to) GLMs (Generalised Linear Models) and tree-based GBMs (Gradient … junior team members’ work, provide feedback, and suggest improvements. Experience of using software such as Python or WTW Radar to analyse data and create predictive models, preferably in a team environment. Proficiency in Excel and MS Office applications. Enthusiasm to maintain and improve your knowledge of data science ...

Title Data Scientist Location Bexhill/Leicester/London – Hybrid Role Purpose The Data Scientist will assist in the design, development, and deployment of predictive models that feed into Hastings’ market‐leading pricing activities. This role is within a team of Data Scientists championing machine learning (ML) techniques … improve predictive performance using vast amounts of customer information. Accountabilities Develop and support predictive models to assess insurance risk and inform pricing and underwriting decisions. Contribute to the integration of models into production systems and support their ongoing monitoring and maintenance. Develop, maintain and improve reusable tools, pipelines ...

technology will underpin our ability to deliver our strategic plan and this role is key to helping us achieve this. Responsibilities Developing and enhancing predictive models Building new, and enhancing existing, predictive models will be a core part of the role. This could include: Cleaning and analysing large … data sets to prepare data to build new predictive models. Building, training and testing new models or techniques to find most appropriate model for the required task. Ensure results are sensible and explainable to non-experts. Large data handling and exploration Working and managing large underwriting data sets ...

join our Systematic Equities team in London. This senior role blends hands-on research with leadership to develop and scale alpha generation and predictive modelling across our global equities portfolio. You will lead the European alpha research effort, manage researchers, and drive a portfolio of high-impact initiatives ...

fiat transactions fiat to crypto transactions (mainly stablecoins) crypto to crypto transactions card spends Define and evolve Transaction Monitoring rules, scenarios, risk typologies and predictive AI models aligned with different compliance frameworks, taking into account Crypto Travel Rule requirements. Drive improvements in False positive reduction, Alert quality, Operational scalability. … with first line and second line operational and compliance teams to ensure controls are effective, explainable, audit‐ready. Partner with Data Science teams on predictive AI models for transactions; model inputs, outputs, and thresholds (you are not expected to build machine learning models, but you must understand how predictive ...

data transformation layer (post-event bus) in Databricks. Move from ad-hoc scripts to software engineering standards (CI/CD, testing, modular code). Modelling Implementation: Support the implementation of the “Unified Name Space” (UNS) across the data estate, to include schema and path standardisation; machine hierarchies and semantic … Analytics (via Databricks/MLflow), unblocking the Data Science team. Mentorship: Upskill the existing team in good practices (dbt, git workflows, SQL optimisation, data modelling). Experience & Background Pragmatic Architect: Capable of making trade-offs between “academic perfection” and “business value”. They must align architecture ...