2 of 2 Contract Customer Segmentation Jobs in the UK

Customer Insight Analyst- Loyalty - Retail - £500-£550 pd via Umbrella Initially for 6 months Hampshire- Hybrid- A couple of days per month required onsite Global Retail company is looking to recruit a Customer Insight Analyst to support the development and delivery of a new loyalty proposition. This role is centred on delivering high-quality analysis and actionable insights … to shape loyalty strategy, inform proposition design, enhance customer engagement, and programme performance. Skills/experience: Extensive experience in an analytical role, with strong proficiency in SQL and ideally working knowledge of Python or R. Demonstrated ability to work with customer data in the context of loyalty, CRM, or marketing programs-generating insights that boost customer retention … engagement, and value. Experience of working with large amounts of data Skilled in designing and evaluating loyalty propositions, including financial modelling, customer segmentation, and benefit testing. Experience of Databricks, Snowflake, or BigQuery. Proven track record in measuring campaign Excellent communications skills #customerdata #insightanalyst #dataanalyst #CRM #loyalty #analyst #sql #databricks Reasonable Adjustments: Respect and equality are core values to More ❯

AI and Machine Learning solutions to solve complex challenges across our banking, financial services, and fintech operations. You will be instrumental in driving revenue growth, optimizing risk management, enhancing customer experiences, and ensuring regulatory compliance on a global scale. Key Responsibilities End-to-End Model Development: Lead the entire ML lifecyclefrom problem framing, data exploration, and feature engineering to … Design: Develop and implement sophisticated machine learning algorithms (e.g., Gradient Boosting, NLP, Deep Learning, Graph Analytics, Reinforcement Learning) for use cases such as fraud detection, credit scoring, algorithmic trading, customer segmentation, and sentiment analysis. Stakeholder Management: Collaborate closely with business leaders (e.g., Risk, Marketing, Trading, Operations) to translate complex business problems into actionable data science projects with clear … model deployment and lifecycle management. Financial Domain Knowledge: Direct experience with at least two of the following domains: Credit Risk Modeling, Fraud Detection, Anti-Money Laundering (AML), Know Your Customer (KYC), Algorithmic Trading, Customer Lifetime Value (CLV), or Marketing Optimization. Model Risk Management (MRM): Solid understanding of model validation, bias/fairness testing, explainable AI (XAI) techniques, and More ❯