The Data Analysis Specialist 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 Responsibilities

• Performance Measurement and Impact Validation: Ensure programs are measured correctly and results are credible
  • Analyze 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, channel
  • Translate findings into clear “what to do next” implications
• Analysis Execution: Own the data and logic behind every output
  • Write and own SQL queries to extract, join, and validate data across sources
  • Execute recurring and ad hoc analyses for CRM programs (aftersales and retail support)
  • Ensure all outputs are accurate, complete, and aligned to business logic
  • Reproduce results consistently; no one-off logic that cannot be traced
• Insight Generation: Go beyond dashboards; explain what matters
  • Build and maintain reporting outputs (Tableau, Excel, etc.), while highlighting key drivers, anomalies, and performance shifts
  • Provide clear summaries of “what happened” and “why it matters”

• Data Ownership and Quality: Numbers are trusted because you validate them
  • Own QA/QC across datasets, queries, and final outputs
  • Validate campaign counts, audience definitions, and performance metrics
  • Identify and escalate data inconsistencies early
  • Ensure alignment between analytics outputs and campaign execution
• Execution Support Across Teams: Operate within the system, not in isolation
  • Partner with campaign, account, and data teams to support program execution
  • Understand how data flows through systems and where issues can occur
  • Support data pulls, audience validation, and post-campaign analysis
• Structured Problem Solving: Turn ambiguity into clear analysis quickly
  • Break down ambiguous requests into clear analytical steps
  • Investigate discrepancies and performance issues with a methodical approach
  • Prioritize practical answers over perfect ones when timelines require it
• Communication and Deliverables: Make analysis usable
  • Contribute to decks, summaries, and readouts with clear, concise language
  • Present findings internally; support client-facing materials as needed
  • Focus on clarity and accuracy; avoid overcomplicating the message

Working Style and Characteristics

• Owns the numbers end-to-end

  • Doesn’t pass along outputs without validating them. If something looks off, they stop and investigate
• Balances speed with accuracy

  • Moves quickly, but not at the expense of correctness. Knows when something is “good enough” versus when it needs deeper validation
• Comfortable working through ambiguity

  • Can take an unclear question and structure it into a defined analysis without needing step-by-step direction
• Finds the signal, not just the data

  • Doesn’t stop at reporting. Identifies what actually changed and why it matters
• Communicates simply and directly

  • Explains results in plain language. Avoids overcomplicating or hiding behind technical detail
• Stays close to execution

  • Understands how campaigns are actually deployed and checks that analytics reflects reality
• Flags issues early

  • Raises risks, inconsistencies, or gaps before they become problems in client settings