Data Analyst (Revenue, Growth)

About the Company

NDA (NICK Digital Agency) is a digital boutique agency working with B2B clients, e-commerce brands, and digital startups in the DACH market. We build demand generation and performance systems — not one-off campaigns. The team is lean, fully remote, and operates without bureaucracy: direct communication, no account managers, results over process.

We're in an active growth stage and looking for an analyst to own the data layer in our delivery.

About the Role

This is not a dashboarding or reporting role.

Your job is to identify where revenue is lost, explain why it happens, and quantify the business impact. You'll work directly with the founder, get full access to clients' revenue stack (CRM, ad accounts, financials), and own the analytical deliverables that drive client decisions.

You will cover three core products:

• Revenue Architecture Diagnostic
• AI Visibility Audit
• AI Revenue Operations Audit

What You'll Do

• Intake and process data from GA4, CRM, ad accounts, and email platforms
• Build attribution views and detect tracking gaps
• Calculate CAC, LTV, payback period, and margin from real client data
• Run funnel drop-off analysis and revenue leak detection
• Run citation testing for AI Visibility audits — testing how clients appear across AI-driven search platforms (40–60 queries × 5 platforms per audit)
• Support process mapping for AI RevOps audits
• Write revenue audit reports (30–45 pages) and process audit reports (25–35 pages)
• Build ROI projection models in Excel / Google Sheets

Key Expectations

• Own 3–4 client audits in parallel at different stages of delivery
• Work autonomously — no step-by-step guidance, no micromanagement
• Identify both revenue leaks and growth upside — not just surface numbers
• Translate findings into clear, decision-ready business insights
• Back up every recommendation with revenue logic and ROI modeling
• Write well — analytical writing quality directly affects client output quality

Requirements

Must Have

• 3+ years in a performance, growth, or analytics role — B2B, SaaS, or digital agency context
• GA4 at an advanced level: event-based tracking, conversion paths, attribution models — building setups from scratch, not just reading them
• One BI tool (Looker Studio, Metabase, Tableau, or PowerBI) — building self-sufficient dashboards independently
• Excel / Google Sheets advanced: pivot tables, financial modeling, lookups, conditional logic
• Basic SQL: SELECT, JOINs, GROUP BY
• Strong analytical writing — ability to turn data into business-visible, human-readable insights
• Structured analytical thinking with a business-outcomes orientation
• English B2+

Nice to Have

• HubSpot or Salesforce admin-level access
• CRM attribution tools: Dreamdata, HockeyStack, or similar
• Mixpanel or Amplitude
• Basic Python for data wrangling
• GA4 → BigQuery → Looker integration
• SaaS metrics fluency: MRR, NRR, GRR, churn cohorts
• DACH market experience
• German B1+ (German-speaking candidates are prioritized)

This Role Is NOT a Fit If You

• Treat analytics as dashboards and figures without interpretation behind them
• Cannot explain clearly why a channel or funnel step is underperforming
• Rely on pre-built data infrastructure and cannot build setups from scratch
• Are not comfortable working with messy, fragmented, multi-source client data
• Cannot back up recommendations with revenue modeling
• Are looking for a permanent salaried position from day one — this engagement starts as freelance/contractor

Work Conditions

• Format: Fully remote, async-first communication
• Timezone: Ukraine or CET
• Engagement type: Freelance / contractor — starting at ~20 hrs/week, scaling to full load based on delivery performance
• No probation period: The first project is the screen. Results delivered → engagement continues and grows.
• Growth path: Permanent employment (Festanstellung) option opens at the 6+ month mark

Selection Process

1. CV review
2. Recruiter screening call
3. HM Case Interview with CEO — you'll receive a real business dataset before the call (GA4 export + CRM data + ad spend across 2–3 channels) and walk through your findings live. The case covers funnel leak detection, tracking gap identification, and revenue modeling. This replaces a traditional test task.
4. Referral check
5. Offer call

Who We're Looking For

You've worked with fragmented, multi-source client data. You build the infrastructure when it doesn't exist. You know how to turn analytical findings into a story a CEO or CMO will act on — and you can model the revenue impact behind every recommendation. If you need a fully built data stack and a detailed brief to get started, this role isn't the right fit.