5 of 5 Remote Customer Segmentation Jobs in Central London

SENIOR CUSTOMER ANALYST LONDON – HYBRID - 2 DAYS A WEEK IN OFFICE SALARY – £70,000 + BONUS THE COMPANY A leading delivery marketplace connecting millions of customers with thousands of restaurant partners! THE ROLE As a Senior Customer Analyst, you will play a pivotal role in driving customer strategy and lifecycle optimisation across acquisition, retention, and loyalty. You … ll use advanced analytics and data storytelling to influence commercial and marketing decisions that shape customer growth. Key Responsibilities: Analyse and optimise customer behaviour across the lifecycle - acquisition, retention, churn. Deliver actionable insights that influence marketing and growth strategy. Run A/B and multivariate tests to evaluate campaign performance. Use SQL and Tableau/Looker to build … by identifying opportunities to move customers through key stages. Collaborate cross-functionally with analytics, marketing, and commercial teams. YOUR SKILLS AND EXPERIENCE Advanced SQL skills essential Strong background in customer, lifecycle, or marketing analytics. Experience owning analytical projects, e.g. customer segmentation, LTV modelling, churn reduction. Strong data storytelling skills - able to translate insights into commercial impact. Ideally More ❯

compliance, and differentiation. You’ll collaborate across product, marketing, sales, and compliance teams to ensure new payment solutions are positioned effectively and meet regulatory standards including KYC (Know Your Customer) , KYB (Know Your Business) , and AML (Anti-Money Laundering) . Key Responsibilities Market Analysis: Research competitive landscapes, customer needs, and emerging trends in payments. Customer & Industry Insight … and feedback, shaping product features and solutions. Product Positioning: Define and communicate the unique value proposition, highlighting differentiators vs. competitors. Pricing Strategy: Develop pricing models aligned with market standards, customer value, and adoption goals. Distribution Strategy: Identify and optimise customer channels, including digital platforms, mobile apps, and strategic partnerships. Marketing & Communications: Collaborate with marketing to build compelling messaging … campaigns, and product collateral. Sales Enablement: Equip sales teams with training, tools, and resources to successfully sell new payment solutions. Launch Execution: Lead product rollouts, customer onboarding, and adoption tracking. Compliance Integration: Ensure go-to-market strategies and product features align with KYC, KYB, and AML requirements. Performance Monitoring: Track KPIs such as acquisition, transaction volume, and revenue to More ❯

compliance, and differentiation. You’ll collaborate across product, marketing, sales, and compliance teams to ensure new payment solutions are positioned effectively and meet regulatory standards including KYC (Know Your Customer) , KYB (Know Your Business) , and AML (Anti-Money Laundering) . Key Responsibilities Market Analysis: Research competitive landscapes, customer needs, and emerging trends in payments. Customer & Industry Insight … and feedback, shaping product features and solutions. Product Positioning: Define and communicate the unique value proposition, highlighting differentiators vs. competitors. Pricing Strategy: Develop pricing models aligned with market standards, customer value, and adoption goals. Distribution Strategy: Identify and optimise customer channels, including digital platforms, mobile apps, and strategic partnerships. Marketing & Communications: Collaborate with marketing to build compelling messaging … campaigns, and product collateral. Sales Enablement: Equip sales teams with training, tools, and resources to successfully sell new payment solutions. Launch Execution: Lead product rollouts, customer onboarding, and adoption tracking. Compliance Integration: Ensure go-to-market strategies and product features align with KYC, KYB, and AML requirements. Performance Monitoring: Track KPIs such as acquisition, transaction volume, and revenue to More ❯

OVERVIEW We are super excited to be partnering with one of the largest global lifestyle brands at a pivotal stage in their data journey. As they bring CRM and customer insight capability 'in house' and roll out a new customer data platform, this role will be central to shaping how data science is delivered, working closely with Data … looking for a passionate and experienced Senior Data Scientist/Manager to lead personalization efforts within their CRM ecosystem. You’ll develop predictive models and recommendation systems that enhance customer engagement across global markets. THE ROLE Lead development of machine learning solutions for CRM personalization. Build and optimize recommendation engines using neural networks and deep learnings, incorporating product embeddings … and other advanced features to improve relevance and performance. Collaborate with CRM and regional marketing teams to align with campaign goals and customer segmentation strategies Own the full ML lifecycle—from model design to deployment and monitoring. Partner with engineering and data teams to ensure scalable solutions. Continuously monitor and improve model performance using data insights and feedback. More ❯

OVERVIEW We are super excited to be partnering with one of the largest global lifestyle brands at a pivotal stage in their data journey. As they bring CRM and customer insight capability 'in house' and roll out a new customer data platform, this role will be central to shaping how data science is delivered, working closely with Data … looking for a passionate and experienced Senior Data Scientist/Manager to lead personalization efforts within their CRM ecosystem. You’ll develop predictive models and recommendation systems that enhance customer engagement across global markets. THE ROLE Lead development of machine learning solutions for CRM personalization. Build and optimize recommendation engines using neural networks and deep learnings, incorporating product embeddings … and other advanced features to improve relevance and performance. Collaborate with CRM and regional marketing teams to align with campaign goals and customer segmentation strategies Own the full ML lifecycle—from model design to deployment and monitoring. Partner with engineering and data teams to ensure scalable solutions. Continuously monitor and improve model performance using data insights and feedback. More ❯