Experian

Senior Data Analyst - SME CRM

Brazil

São Paulo, São Paulo, Brazil

PythonSQL
Automatic translation. Check the original.

Company Description

Experian is a global data and technology company that powers opportunities for people and businesses around the world. We operate in various markets, such as financial services, healthcare, automotive, agribusiness, insurance, among others. Experian invests in people and new advanced technologies to unlock the power of data. We have an incredible team of 25,200 employees in 32 countries.

Our uniqueness is valuing yours. Experian's people-centric, inclusive, and purpose-driven culture is recognized by numerous awards—including World’s Best Workplaces™ 2025 (Fortune's Top 25 global) and Great Place To Work™ in 26 countries, among others. Check out Experian Life on social media or explore our careers site to understand why. Experian is also proud to be an equal opportunity and affirmative action employer.

Job Description

We are looking for someone to act as a Senior Data Analyst – SME CRM, with a strategic role in the evolution of analytical intelligence applied to SME customer relationships. This position will be responsible for connecting data, customer behavior, journeys, campaign performance, and analytical recommendations to CRM decisions, supporting more personalized, relevant, and results-oriented actions.

The individual will play an essential role in bridging SME CRM and the NBO/NBA models—Next Best Offer and Next Best Action—already developed by the Data Science team. Their role will be to translate model outputs into CRM hypotheses, communication opportunities, actionable audiences, structured tests, and analyses that facilitate the adoption of intelligence in journeys, campaigns, and relationship channels.

This person will partner with CRM, Marketing, Sales, Product, Data Science, Analytics, Channels, and Technology, contributing to transforming analytical intelligence into practical actions that increase engagement, conversion, retention, monetization, product penetration, and customer value.

We are looking for a senior, analytical, strategic, and impact-oriented individual, capable of acting as a business partner in identifying opportunities, prioritizing actions, and evolving intelligence applied to SME CRM.

This person will not be responsible for developing NBO/NBA models, but will play an essential role in connecting existing models to CRM operations, transforming analytical recommendations into hypotheses, tests, campaigns, journeys, and actionable learnings.

We expect someone with analytical depth, business vision, and influencing capacity to help the team better adopt the use of intelligence in communications, making interactions with SME customers more relevant, personalized, measurable, and efficient.

Qualifications

What we look for in you:

  1. Solid experience in data analysis, CRM analytics, marketing analytics, customer intelligence, lifecycle analytics, or related areas.
  1. Advanced proficiency in SQL for extracting, treating, analytically modeling, and cross-referencing large volumes of data.
  1. Advanced knowledge of Excel or Google Sheets.
  1. Experience with BI and data visualization tools, such as Power BI, Tableau, Looker, or similar.
  1. Experience with lifecycle analysis, cohorts, funnels, segmentation, clusters, behavior, propensity, and campaign performance.
  1. Consistent knowledge of CRM metrics, digital marketing, retention, churn, LTV, conversion, engagement, usage frequency, product penetration, and incrementality.
  1. Familiarity with NBO/NBA applications, propensity models, offer recommendation, audience prioritization, and journey personalization.
  1. Experience in translating analytical outputs or predictive models into actionable communication, segmentation, and relationship strategies.
  1. Experience with A/B testing, control groups, impact measurement, basic statistical reading, and experimentation methodologies.
  1. Knowledge of CRM platforms, marketing automation, or MarTech, such as Salesforce, Adobe Campaign, Braze, Oracle, RD Station, or similar.
  1. Knowledge of Python, R, or other data analysis languages will be considered a plus.

Soft Skills

  1. Advanced analytical thinking and ability to structure complex problems.
  1. Strategic business vision, with the ability to connect data, customers, products, channels, and financial results.
  1. Ability to act as a bridge between technical and business areas.
  1. Strong communication skills to translate analyses, models, and recommendations into clear actions for CRM and stakeholders.
  1. Investigative curiosity, critical thinking, and a consultative approach.
  1. Proactivity in identifying opportunities, risks, inconsistencies, and paths for evolution.
  1. Ability to influence decisions based on evidence, tests, and results.
  1. Organization, autonomy, and responsibility for high-impact business deliverables.
  1. Collaboration to work in cross-functional environments with CRM, Marketing, Sales, Product, Data Science, Analytics, and Technology.
  1. Results orientation, with a focus on impact, continuous learning, and performance improvement.
  1. Desirable experience with CDPs, CRM datamarts, data-channel integration, predictive models, or recommendation engines.

Differentiators

  1. Previous experience with B2B CRM, SMEs, financial services, credit, collections, data, marketing services, or digital products.
  1. Experience with Next Best Offer, Next Best Action strategies, offer recommendation, advanced personalization, or lifecycle marketing.
  1. Experience in activating analytical models in campaigns, journeys, digital channels, or sales actions.
  1. Experience with Salesforce, CDPs, automation tools, data platforms, or integration between analytical models and activation channels.
  1. Knowledge in portfolio analysis, product penetration, portfolio expansion, cross-sell, upsell, and base monetization.
  1. Experience in environments driven by revenue, conversion, retention, sales efficiency, and campaign performance goals.

Main Responsibilities: Strategy, CRM, and Business

  1. Support the evolution of SME CRM strategy based on data, customer behavior, lifecycle, campaign performance, and business opportunities.
  1. Connect customer analyses to acquisition, activation, engagement, retention, reactivation, cross-sell, upsell, retention, and churn reduction strategies.
  1. Identify opportunities for personalizing communications, offers, and journeys based on profile, segment, channel, contracted product, behavior, customer maturity, and relationship stage.
  1. Translate complex analyses into practical recommendations for CRM, Marketing, Sales, Product, and other stakeholders.
  1. Support the definition of audiences, journeys, hypotheses, messages, channels, and approach moments based on evidence and data.
  1. Contribute to the evolution of CRM indicators, such as engagement, conversion, revenue, retention, churn, reactivation, product penetration, LTV, customer value, and campaign efficiency.
  1. Act as an analytical reference for SME CRM decisions, helping to elevate the quality of hypotheses, results interpretation, and the team's data-driven culture.

Connection with NBO/NBA and Intelligence Applied to CRM

  1. Act as a bridge between the SME CRM team and the Data Science team responsible for NBO/NBA models.
  1. Interpret NBO/NBA model outputs and translate them into actionable opportunities for campaigns, journeys, automated sequences, digital channels, and sales actions.
  1. Support the definition of hypotheses for model usage in communications, considering audience, offer, recommended action, channel, message, frequency, and approach moment.
  1. Propose A/B tests, incrementality tests, pilots, and controlled experiments to evaluate the effectiveness of NBO/NBA usage in CRM actions.
  1. Build analyses that facilitate the adoption of intelligence in communications, demonstrating gains, learnings, limitations, and opportunities for evolution.
  1. Monitor the performance of actions using NBO/NBA, evaluating engagement, conversion, revenue, offer acceptance, product usage, retention, cross-sell, upsell, and incremental impact.
  1. Identify response patterns by segment, product, channel, journey stage, and recommendation type, generating learnings for continuous optimization.
  1. Support audience and recommendation prioritization, connecting the model's analytical rationale with the real needs of SME CRM and business.
  1. Work with Data Science to feed back learnings from CRM, campaign results, response behavior, and operational opportunities into the models.
  1. Ensure that NBO/NBA usage is practical, measurable, and aligned with the SME customer relationship strategy.

Analytical Operation, Data, and Processes

  1. Lead analyses of customer base, cohorts, funnels, journeys, channels, products, clusters, behavior, propensity, and campaign performance.
  1. Build and evolve dashboards, executive reports, and recurring analytical views for SME CRM monitoring.
  1. Support the structuring of analytical databases, segmentations, eligibility rules, prioritization criteria, and opportunity studies.
  1. Ensure clarity, reliability, and actionability of indicators used in CRM decisions.
  1. Work with different data sources to build a more integrated customer view, considering relationship, consumption, engagement, sales history, channel interactions, and contracted products.
  1. Identify inconsistencies, data gaps, automation opportunities, and improvements in CRM analytical processes.
  1. Contribute to reducing communication overlap, improving contact pressure, and increasing the relevance of interactions.
  1. Support the evolution of automated, dynamic, and customer-behavior-responsive journeys.
  1. Contribute to greater operational efficiency of campaigns, segmentations, and performance analyses.

Measurement, Experimentation, and Learnings

  1. Define and conduct performance analyses to evaluate the impact of campaigns, journeys, automated sequences, offers, sales actions, and intelligence-driven communications.
  1. Structure A/B tests, multivariate tests, control groups, and incrementality analyses, whenever applicable.
  1. Evaluate business hypotheses with analytical rigor, connecting results to clear learnings and optimization recommendations.
  1. Measure the impact of CRM actions on indicators such as conversion, revenue, engagement, product usage, retention, churn, cross-sell, upsell, and LTV.
  1. Create analytical narratives that facilitate decision-making by different audiences, from technical teams to business leadership.
  1. Transform complex data into diagnoses, recommendations, and action plans.
  1. Document learnings about what works, for which audiences, on which channels, at which journey stages, and with which types of recommendations.
  1. Support the creation of a continuous learning routine, connecting hypotheses, tests, results, and next steps.

Additional Information

Experian is a global data and technology company that powers opportunities for people and businesses around the world. We operate in various markets, such as financial services, healthcare, automotive, agribusiness, insurance, among others. Experian invests in people and new advanced technologies to unlock the power of data. We have an incredible team of 25,200 employees in 32 countries.

Our uniqueness is valuing yours. Experian's people-centric, inclusive, and purpose-driven culture is recognized by numerous awards—including World’s Best Workplaces™ 2025 (Fortune's Top 25 global) and Great Place To Work™ in 26 countries, among others. Check out Experian Life on social media or explore our careers site to understand why. Experian is also proud to be an equal opportunity and affirmative action employer.

Experian Careers - Creating a better tomorrow together

Find out what its like to work for Experian by clicking here

Employee Status: Regular

Role Type: Home

Department: Marketing and Communications

Schedule: Full Time

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