Analista de Dados Sênior - CRM PME

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Analista de Dados Sênior - CRM PME based in Brazil.

This is a senior data and CRM analytics role focused on turning customer intelligence into measurable business impact across the SME segment. You’ll connect customer behavior, lifecycle insights, campaign performance, and analytical recommendations to CRM strategy and execution. A key part of the role is bridging existing Next Best Offer (NBO) and Next Best Action (NBA) models with practical CRM activation. You’ll translate analytical outputs into audiences, hypotheses, experiments, campaigns, journeys, and actionable recommendations. Working across CRM, Marketing, Commercial, Product, Data Science, Analytics, Channels, and Technology, you’ll influence decisions through evidence and experimentation. The role combines advanced analytics with strong business acumen, requiring someone who can simplify complex insights and drive adoption across stakeholders. You’ll play a central role in making customer interactions more personalized, relevant, measurable, and effective while strengthening a data-driven CRM culture.

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.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1