76 to 100 of 117 Permanent Customer Analytics Jobs

Look is a feel-good fashion brand seeking a data analytics specialist to turn customer data into actionable insights across acquisition, retention, loyalty and value. You will build models, dashboards and reports to guide business decisions in a fast-paced retail environment. You'll apply statistical techniques, work … with SQL, Python or R, and collaborate with cross-functional teams to drive improvements in customer engagement and profitability. #J-18808-Ljbffr ...

strategy to reality by taking a pragmatic and practical approach to build solutions that last. We're seeking a Director in London in Data & Analytics to help us take vision to value and create lasting impact. YOU WILL: Scoping, selling, architecting and delivering a wide variety of Data & Analytics … build new client relationships with some of the most exciting brands in the world. Shape the future by being part of the Data & Analytics global leadership team. Be a thought leader by contributing to blog postings, white papers, pod casts. Be part of the global thought leadership team ...

Architect and oversee the integration of marketing technologies, ensuring seamless data flow across paid marketing channels (SEM, Paid Social, Display, Affiliates etc), web & app analytics, CRM and personalization platforms. Partner with marketing, product, and engineering teams to define and implement scalable solutions that improve audience & value signals, attribution … optimization. Define best practices, governance frameworks, and training programs to enhance marketing tech & AI adoption across teams. Help Farfetch in driving towards a single customer view across all touchpoints and parts of the journey Work with marketing & product teams to optimise our product feeds with rich & accurate data ...

Architect and oversee the integration of marketing technologies, ensuring seamless data flow across paid marketing channels (SEM, Paid Social, Display, Affiliates etc), web & app analytics, CRM and personalization platforms. Partner with marketing, product, and engineering teams to define and implement scalable solutions that improve audience & value signals, attribution … optimization. Define best practices, governance frameworks, and training programs to enhance marketing tech & AI adoption across teams. Help Farfetch in driving towards a single customer view across all touchpoints and parts of the journey Work with marketing & product teams to optimise our product feeds with rich & accurate data ...

services and solutions to reinvent client business models, drive better outcomes and unlock growth with speed. Bringing together domain expertise with robust data, powerful analytics, cloud and AI to create agile, scalable solutions and execute complex operations for the world’s leading corporations. EXL was founded on the core … role: We’re looking for a highly skilled Azure Databricks Data Engineer to design, develop and deliver cloud-based data integration and analytics solutions within our Retail portfolio . You’ll work across data engineering, modelling and transformation initiatives, building scalable pipelines, optimising performance and ensuring best practices ...

aesthetic that embodies luxury with an emphasis on craftsmanship, innovation and compelling fashion movements. Job Description As a Product Manager within our COS AI, Analytics and Data (AIAD) team, you will play a pivotal role in driving the development, implementation, and management of data & insights products for global COS. … Data Engineers, closely engaging with key stakeholders to deliver high-quality AI, data & insights products for Global COS. You will lead our Customer Experience (CX) and marketing analytics suite, which includes overseeing and driving the vision, delivery, and lifecycle of data & insights products across three dedicated product teams ...

developing a data culture and demonstrating the value of data in our decision making Lead our efforts to develop the data science (and broader customer analytics) brand at our client for both internal and external audiences Proven experience delivering high-quality AI-based products and productionisation of Machine …/AI services suing Kubernetes & KubeFlow Strong management and leadership skills previous experience managing a team Strong influencing, communication and stakeholder management skills Be Customer Focused constantly improving our customers experience We listen to our customers and colleagues We innovate products and experiences to stay ahead Be Human leading ...

developing a “data culture” and demonstrating the value of data in our decision making Lead our efforts to develop the data science (and broader customer analytics) “brand” at our client for both internal and external audiences Proven experience delivering high-quality AI-based products and productionisation of Machine …/AI services suing Kubernetes & KubeFlow Strong management and leadership skills – previous experience managing a team Strong influencing, communication and stakeholder management skills Be Customer Focused – constantly improving our customers' experience We listen to our customers and colleagues We innovate products and experiences to stay ahead Be Human – leading ...

publishers - the Financial Times - is recognised as an innovator within the media industry, pioneering successful new digital business models and delivery. Within this dynamic, customer-centric organisation reacting to a fast-moving digital environment, the Customer Analytics team plays a pivotal role in driving the success … helping to shape all areas of our multichannel strategy. Over the past 10 years, the Analytics team has established itself as an independent source of truth and strategic advice for the whole business, providing actionable insight to a variety of digital stakeholders across the business (i.e. Marketing, Product, Editorial ...

developing a "data culture" and demonstrating the value of data in our decision making Lead our efforts to develop the data science (and broader customer analytics) "brand" at Kingfisher for both internal and external audiences What you'll bring Proven experience delivering high-quality AI-based products …/AI services suing Kubernetes & KubeFlow Strong management and leadership skills - previous experience managing a team Strong influencing, communication and stakeholder management skills Be Customer Focused - constantly improving our customers’ experience We listen to our customers and colleagues We innovate products and experiences to stay ahead Be Human - leading ...

developing a “data culture” and demonstrating the value of data in our decision making. Lead our efforts to develop the data science (and broader customer analytics) “brand” at Kingfisher for both internal and external audiences. Qualifications Proven experience delivering high-quality AI‐based products and productionisation of Machine ...

Dunelm is seeking a Senior Analyst to deliver high-impact analytics that inform decisions across a £2bn omnichannel business. You’ll own end-to-end analytics projects, turning data into actionable recommendations to help the business grow. Collaborating with stakeholders across commercial, ecommerce, finance and operations ...

document and map KPIs, metrics and critical data elements across reporting and operational processes. Work closely with business stakeholders, including sales teams, to understand customer data requirements and reporting needs. Map reporting requirements back to source systems, data feeds and data warehouse structures within GCP.Support the development of data … data quality rules and collaborate with the GCP engineering team to implement governance and quality controls using dbt. Support data catalogue, finance process and customer data mapping activities across the wider GCP data platform. Act as the bridge between end users and technical teams, ensuring business requirements are accurately ...

growing client demand for advanced AI and data science solutions. The ideal candidate will have a deep understanding of artificial intelligence, machine learning and analytics, combined with IT consulting experience and domain expertise in financial services. In this role, you will partner with clients to solve complex business challenges … services, focusing on risk, compliance, and operational efficiency Design and deploy AI-enabled solutions for use cases such as credit scoring, fraud detection, and customer analytics Implement AI governance frameworks including compliance with Basel III, GDPR, and ethical AI practices Lead deployment of MLOps pipelines to transition models ...

problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction. Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion ...

problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction. Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion ...

extraction. Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility. Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion ...

extraction. Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility. Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion ...

extraction. Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility. Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion ...

extraction. Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility. Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion ...

extraction. Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility. Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion ...

extraction. Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility. Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion ...

extraction. Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility. Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion ...

extraction. Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility. Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion ...

extraction. Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility. Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion ...