Senior Data Analyst - CRM

Senior Data AnalystThe Senior Data Analyst is responsible for turning CRM and marketing data into clear, defensible business decisions.This role executes analysis with precision while identifying what is working, what is not, and where programs should adjust. This role sits at the center of delivery; ensuring data is accurate, analysis is sound, and outputs are ready to inform decisions.You will support one of our client's CRM programs across aftersales and retail touchpoints, working across data, analytics, and account teams to ensure programs are measurable, accurate, and improving over time. This is a high-accountability execution role. You are expected to deliver accurate analysis, surface key insights, and ensure outputs are ready to inform decisions.Core ResponsibilitiesPerformance Measurement and Impact Validation: Ensure programs are measured correctly and results are credibleAnalyze CRM performance across channels (direct mail, email, digital)Apply structured measurement approaches (test vs control, pre/post, matched comparisons where applicable)Identify drivers of performance; audience, offer, timing, channelTranslate findings into clear "what to do next" implicationsAnalysis Execution: Own the data and logic behind every outputWrite and own SQL queries to extract, join, and validate data across sourcesExecute recurring and ad hoc analyses for CRM programs (aftersales and retail support)Ensure all outputs are accurate, complete, and aligned to business logicReproduce results consistently; no one-off logic that cannot be tracedInsight Generation: Go beyond dashboards; explain what mattersBuild and maintain reporting outputs (Tableau, Excel, etc.), while highlighting key drivers, anomalies, and performance shiftsProvide clear summaries of "what happened" and "why it matters"Data Ownership and Quality: Numbers are trusted because you validate themOwn QA/QC across datasets, queries, and final outputsValidate campaign counts, audience definitions, and performance metricsIdentify and escalate data inconsistencies earlyEnsure alignment between analytics outputs and campaign executionExecution Support Across Teams: Operate within the system, not in isolationPartner with campaign, account, and data teams to support program executionUnderstand how data flows through systems and where issues can occurSupport data pulls, audience validation, and post-campaign analysisStructured Problem Solving: Turn ambiguity into clear analysis quicklyBreak down ambiguous requests into clear analytical stepsInvestigate discrepancies and performance issues with a methodical approachPrioritize practical answers over perfect ones when timelines require itCommunication and Deliverables: Make analysis usableContribute to decks, summaries, and readouts with clear, concise languagePresent findings internally; support client-facing materials as neededFocus on clarity and accuracy; avoid overcomplicating the messageQualificationsWorking Style and CharacteristicsOwns the numbers end-to-endDoesn't pass along outputs without validating them. If something looks off, they stop and investigateBalances speed with accuracyMoves quickly, but not at the expense of correctness. Knows when something is "good enough" versus when it needs deeper validationComfortable working through ambiguityCan take an unclear question and structure it into a defined analysis without needing step-by-step directionFinds the signal, not just the dataDoesn't stop at reporting. Identifies what actually changed and why it mattersCommunicates simply and directlyExplains results in plain language. Avoids overcomplicating or hiding behind technical detailStays close to executionUnderstands how campaigns are actually deployed and checks that analytics reflects realityFlags issues earlyRaises risks, inconsistencies, or gaps before they become problems in client settingsRequired qualifications2–4 years in marketing analytics, CRM analytics, or related fieldStrong SQL skills; able to independently extract, join, and validate dataExperience analyzing campaign performance across channelsProven ability to translate data into business insightsExperience working with large datasets and complex data structuresStrong QA mindset; detail-oriented without losing speedClear communication skills; able to simplify complex findingsPreferred qualificationsExperience in automotive, CRM, or lifecycle marketingExposure to test/control design and incrementality measurementExperience with Databricks, Python, or R for deeper analysisFamiliarity with Tableau or similar visualization tools (used for communication, not just reporting)What success looks likeYour insights can lead to changes in targeting, spend, or program structureNumbers are trusted; minimal rework or revalidation neededAnalysis is timely and moves decisions forwardStakeholders rely on you to explain "why" not just "what happened" MSLGROUP