高级数据分析师 - SME CRM

#### Company Description

Experian is a global data and technology company that powers opportunities for people and businesses around the world. We operate in diverse 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 several 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 employer and an affirmative action employer.

#### Job Description

We are looking for a person 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 person will play an essential role in bridging the gap between SME CRM and the NBO/NBA (Next Best Offer and Next Best Action) models already developed by the Data Science team. Your 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 work in partnership with CRM, Marketing, Sales, Product, Data Science, Analytics, Channels, and Technology, contributing to transforming analytical intelligence into practical actions that increase engagement, conversion, retention, profitability, product penetration, and customer value.

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

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

We expect someone with analytical depth, business vision, and the ability to influence 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 are looking for in you:**

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

_Soft Skills_

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

_Preferred Qualifications_

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

**Main Responsibilities Strategy, CRM and Business**

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

_Connection with NBO/NBA and Intelligence Applied to CRM_

- Act as a bridge between the SME CRM team and the Data Science front responsible for **NBO/NBA** models.
- Interpret NBO/NBA model outputs and translate them into actionable opportunities for campaigns, journeys, communication flows, digital channels, and commercial actions.
- Support the definition of hypotheses for using models in communications, considering audience, offer, recommended action, channel, message, frequency, and timing.
- Propose A/B tests, incrementality tests, pilots, and controlled experiments to evaluate the effectiveness of using NBO/NBA in CRM actions.
- Build analyses that facilitate the adoption of intelligence in communications, demonstrating gains, learnings, limitations, and opportunities for evolution.
- Monitor the 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, journey stage, and type of recommendation, generating learnings for continuous optimization.
- Support the prioritization of audiences and recommendations, connecting the model’s analytical rationale to the real needs of CRM and the SME business.
- Work with Data Science to provide feedback to models with CRM learnings, campaign results, response behavior, and opportunities observed in operations.
- Ensure that the use of NBO/NBA is applied in a practical, measurable way that adheres to the SME customer relationship strategy.

_Analytical Operation, Data and Processes_

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

_Measurement, Experimentation and Learnings_

- Define and conduct performance analyses to evaluate the impact of campaigns, journeys, communication flows, offers, commercial actions, and intelligence-driven communications.
- Structure A/B tests, multivariate tests, control groups, and incrementality analyses whenever applicable.
- Evaluate business hypotheses with analytical rigor, connecting results to clear learnings and optimization recommendations.
- Measure the impact of CRM actions on indicators such as conversion, revenue, engagement, product usage, retention, churn, cross-sell, upsell, and LTV.
- Create analytical narratives that facilitate decision-making for different audiences, from technical teams to business leadership.
- Transform complex data into diagnostics, recommendations, and action plans.
- Document learnings about what works, for which audiences, in which channels, at which journey stages, and with which types of recommendations.
- 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 diverse 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 several 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 employer and an affirmative action employer._

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