Accountabilities:

• Support the evolution of the SME CRM strategy using customer data, behavioral insights, lifecycle analysis, campaign performance, and business opportunities.
• Identify opportunities across acquisition, activation, engagement, retention, reactivation, cross-sell, upsell, churn reduction, and customer value expansion.
• Analyze customer profiles, segments, products, channels, behavioral patterns, and relationship maturity to identify opportunities for personalized communications and journeys.
• Translate complex analytical findings into clear, practical recommendations for CRM, Marketing, Commercial, Product, and other business stakeholders.
• Define and refine audiences, journeys, hypotheses, messages, channels, and contact moments based on data and customer insights.
• Act as the analytical reference for SME CRM decisions, helping improve the quality of hypotheses, performance analysis, and data-driven decision-making.
• Partner with Data Science teams as the bridge between NBO/NBA models and CRM operations, ensuring analytical intelligence can be effectively activated.
• Interpret NBO/NBA model outputs and translate recommendations into actionable opportunities for campaigns, journeys, communication rules, digital channels, and commercial initiatives.
• Define use cases for NBO/NBA recommendations, considering target audience, recommended offer or action, channel, message, frequency, and timing.
• Design and support A/B tests, controlled experiments, pilots, and incremental-impact analyses to assess the effectiveness of NBO/NBA-driven CRM initiatives.
• Monitor performance of actions using NBO/NBA, evaluating engagement, conversion, revenue, offer acceptance, product usage, retention, cross-sell, upsell, and incremental impact.
• Identify response patterns by segment, product, channel, customer journey stage, and recommendation type to generate optimization insights.
• Work with Data Science to feed CRM learnings, campaign outcomes, customer responses, and operational insights back into the evolution of analytical models.
• Lead analyses involving cohorts, funnels, customer journeys, channels, products, clusters, behavioral patterns, propensity, and campaign performance.
• Build and enhance dashboards, executive reports, recurring analytical views, and performance monitoring for SME CRM.
• Support the creation of analytical datasets, segmentation rules, eligibility criteria, prioritization frameworks, and opportunity assessments.
• Ensure the accuracy, clarity, reliability, and actionability of CRM metrics and analytical outputs.
• Integrate multiple data sources to develop a broader view of customers, including interactions, products, commercial history, engagement, and channel behavior.
• Identify data inconsistencies, analytical gaps, automation opportunities, and process improvements.
• Help reduce communication overlap and contact pressure while improving the relevance and effectiveness of customer interactions.
• Structure and evaluate A/B tests, control groups, multivariate experiments, and incremental-impact analyses where appropriate.
• Measure the impact of CRM initiatives on conversion, revenue, engagement, product adoption, retention, churn, cross-sell, upsell, and LTV.
• Build compelling analytical narratives that translate complex data into clear diagnoses, recommendations, and action plans.
• Document learnings about which strategies work, for which audiences, through which channels, at which stages of the customer journey, and with which recommendations.
• Promote a continuous learning cycle connecting hypotheses, experiments, results, and optimization opportunities.
• Contribute to a stronger data-driven culture across CRM and partner functions.

Requirements:

• Solid experience in data analytics, CRM analytics, marketing analytics, customer intelligence, lifecycle analytics, or related fields.
• Advanced proficiency in SQL, including data extraction, transformation, analytical modeling, and analysis of large datasets.
• Advanced knowledge of Excel or Google Sheets.
• Experience with BI and data visualization platforms such as Power BI, Tableau, Looker, or equivalent tools.
• Strong experience with lifecycle analysis, cohorts, funnels, segmentation, clustering, customer behavior, propensity, and campaign performance.
• Strong understanding of CRM and marketing metrics, including retention, churn, LTV, conversion, engagement, product penetration, frequency of use, and incremental impact.
• Familiarity with NBO/NBA, propensity models, offer recommendations, audience prioritization, and personalized customer journeys.
• Proven ability to translate analytical or predictive-model outputs into actionable communication, segmentation, and customer relationship strategies.
• Experience designing or analyzing A/B tests, control groups, impact measurement, and experimentation frameworks, with a solid understanding of basic statistics.
• Experience with CRM, marketing automation, or MarTech platforms such as Salesforce, Adobe Campaign, Braze, Oracle, RD Station, or similar solutions.
• Knowledge of Python, R, or another data analysis language is a plus.
• Experience with CDPs, CRM datamarts, data-to-channel integrations, predictive models, or recommendation engines is desirable.
• Strong strategic and analytical thinking, with the ability to structure complex problems and connect data to business outcomes.
• Strong communication skills and the ability to act as a bridge between technical teams and business stakeholders.
• Consultative mindset, curiosity, critical thinking, and a proactive approach to identifying opportunities and risks.
• Ability to influence decisions through evidence, experimentation, and measurable results.
• Strong organization, autonomy, ownership, and ability to manage high-impact analytical initiatives.
• Comfortable collaborating across CRM, Marketing, Commercial, Product, Data Science, Analytics, Channels, and Technology teams.
• Experience with B2B CRM, SME customers, financial services, credit, collections, data, marketing services, or digital products is a plus.
• Experience with Next Best Offer, Next Best Action, advanced personalization, lifecycle marketing, or recommendation strategies is desirable.
• Knowledge of portfolio analysis, product penetration, customer expansion, cross-sell, upsell, and customer profitability is advantageous.

Benefits:

• Opportunity to work on strategic CRM, customer intelligence, and data-driven initiatives with significant business impact.
• Exposure to advanced analytical applications including NBO/NBA, personalization, experimentation, and predictive intelligence.
• Cross-functional collaboration with CRM, Marketing, Commercial, Product, Data Science, Analytics, Channels, and Technology teams.
• Professional growth in a data- and technology-driven environment.
• Opportunities to influence strategic customer and business decisions through analytics.
• Inclusive, people-centered working environment.
• Equal-opportunity workplace committed to diversity, inclusion, and professional development.
• Opportunities to work with large-scale data and advanced technologies across multiple industries and use cases.