245 jobs for “data warehouse”
Harnham - Data and Analytics Recruitment London £50,000 – £60,000 pa
This role involves leading analytics across supply, inventory, and operations, including stock levels, warehouse flows, and fulfilment performance. You will optimise warehouse capacity, conduct cost analysis, design A/B tests, and mentor junior analysts while partnering with senior stakeholders to shape operational strategy.
Michael Page Birmingham £85,000 – £95,000 pa
Lead enterprise-wide data and analytics capability for a large social housing organisation on a 12-month fixed term contract. Own the data strategy, governance framework, enterprise data architecture and BI/analytics delivery, while leading a data function and advising executive and senior leadership teams. Requires one day per week onsite at the Birmingham head office.
Harnham - Data and Analytics Recruitment London £45,000 – £55,000 pa
Hands-on engineering role building proprietary tools, API connectors into BigQuery, serverless applications and AI-enabled marketing dashboards for an agency's Media Solutions team. Works across SEO, paid search, paid social and content, collaborating with data specialists and stakeholders to scope and ship scalable technical products.
Bowers Partnership London £825 pd
Hands-on VP-level data scientist building generative AI, LLM/NLP and statistical modelling products end to end for a boutique investment bank's M&A and advisory bankers. Works in a small team taking prototypes into production, writing production-quality Python and explaining models to senior non-technical stakeholders. M&A experience is essential.
Spencer Rose Bristol £450 – £480 pd
Designs, builds and deploys end-to-end AI/ML solutions for a banking client's Coach AI programme, including LLM-powered assistants, copilots and multi-agent agentic systems. The role covers ML pipelines, MLOps deployment, NLP, computer vision and voice AI, plus AI guardrails, responsible-AI governance and mentoring a team as senior lead.
Opus Recruitment Solutions London £260 – £290 pd
Two Data Analysts are sought to support analytical and reporting initiatives in a payments, banking or fintech context. Day to day involves backbook segmentation, customer analytics, propensity and predictive modelling, performance reporting, and building and automating dashboards and MI. The role requires strong SQL and Power BI or Tableau skills, working with large datasets and stakeholders to turn business requirements into analytical solutions.
Michael Page Leeds £40,000 – £48,000 pa
Analyse large datasets to uncover trends and build predictive models and algorithms that support strategic decisions in a financial services setting. Work within a collaborative analytics team, presenting findings to non-technical stakeholders and helping maintain data pipelines and infrastructure. Requires Python, R or SQL plus statistical and machine learning techniques, with GIS tooling also desirable.
Capital One Mansfield
Develops and maintains the statistical and machine learning models behind customer lending and underwriting decisions, using advanced feature generation and large-scale data manipulation. Consults on complex statistical test design and works cross-functionally with business partners, with a strong emphasis on Model Risk Management, validation and monitoring. Python coding and Open Banking or Credit Bureau data experience are central.
Capital One Nottingham
Develops and maintains the statistical and machine learning models behind customer lending and underwriting decisions, using advanced feature generation and large-scale data manipulation. Consults on statistical test design and works cross-functionally with business partners, with a strong emphasis on Model Risk Management, validation and monitoring.
ARM Manchester
Day-to-day work centres on analysing and reconciling large finance datasets in SQL, investigating data quality issues across multiple systems, and defining business rules, mappings and acceptance criteria. The role also covers testing, validation and release support, producing analysis for technical and non-technical stakeholders while working with finance, risk, data and technology teams.
NES Group Ltd London
Leads customer analytics across multiple markets, building CLV, RFM segmentation, incrementality measurement and value frameworks that give leadership defensible commercial insight. Partners with Finance to reconcile customer, transaction and margin data, and builds scalable pipelines in Databricks, Spark and Python with strong validation and audit practices.
DCV Technologies Manchester £550 – £600 pd
Contract role developing and evaluating AI/ML solutions, including classical models and LLM-based applications on Google Cloud Platform. Involves prompt engineering, RAG concepts, experiment design, model evaluation and documentation, plus requirements gathering, code review and troubleshooting alongside project managers and developers.
BDO London
Builds and productionises AI/ML models for a regulated financial client, covering data wrangling, feature engineering, model development and validation, and containerised deployment. Works with an existing delivery team on classification, outlier detection, ranking and time-series risk analysis, with documentation and reproducible Git-based workflows. RegTech, FinCrime and graph analytics experience is advantageous.
Vallum Associates London £475 – £500 pd
Data scientist role focused on collecting and analysing large datasets, building experimental models and machine learning applications in Python, and performing complex statistical analysis. Involves leading small teams, mentoring junior data scientists, and working with classical ML, LLMs, prompt/RAG techniques and experiment design. Contract position with two days per week in the London office.
Amazon London
Hands-on analysis and modelling of large multimodal datasets to measure and improve conversational shopping systems built on LLMs, information retrieval, recommender systems and knowledge graphs. Designs and analyses A/B tests, builds metrics and dashboards, and develops predictive models, working with scientists and engineers in a London team of around 150.
