Overview:
The Revenue Operations Analyst is a pivotal member of a sales-oriented organization, providing actionable data intelligence that links client activity to revenue outcomes. This role designs, manages, and continuously improves live dashboards and playbooks used by Sales, Marketing, and Product teams to make data-d-riven decisions in real time.
Key Description:
1. Data Infrastructure & Analytics
- Design, build, and own live dashboards tracking client‑level KPIs: AUM, net funds flow, realised P&L, funding‑rate costs, margin utilisation, and liquidation flags
- Document all data definitions and methodologies are consistent across organisation
- Guide internal stakeholders toward scalable, templatised solutions
- Monitor dashboards daily, set anomaly alerts, and produce call sheets prioritising revenue‑impact client outreach (e.g. clients with 15% spike in funding costs)
- Quantify incremental revenue tied to each alert to illustrate tangible impact on the desk
- Maintain market‑wide views including open interest, perp‑spot basis, funding curves, volume, and volatility clusters
- Provide bespoke data pulls, charts, and one‑pagers for live deals or urgent client asks
- Refactor frequent analyses into self‑serve views and maintain an open backlog of requests ranked by revenue impact and effort
2. Revenue Enablement & Insights
- Co‑design reusable battle cards, account health snapshots, and funding‑rate forecast sheets covering ≥ 80% of recurring prospect and renewal scenarios
- Deliver concise pre‑market “market movers” briefs highlighting client‑specific talking points
- Conduct periodic training to Sales including walkthroughs or video tutorials on the dashboards and revenue enablement tools built
3. Client Engagement & Cross‑Functional Impact
- Partner with Marketing and Product to measure campaign lift, A/B test results, and onboarding effectiveness; present clear ROI calculations recommending scale‑up or sunset actions
- Prepare a 10‑minute weekly data segment for Revenue Leadership focusing on recent movements, implications, and recommended actions
- Translate complex metrics into plain‑English narratives that drive decisions, not debates.
- Engage directly with clients to provide market colour and insights into their trading statistics
Education and Qualifications:
- Bachelor’s or Master’s degree in Finance, Economics, Data Science, or related field
- 2–5 years of experience in revenue operations, data analytics, or business intelligence—preferably in trading, fintech, or exchange environments
- Proficiency in SQL, Python (Pandas), and BI tools (e.g., Power BI, Grafana, Tableau, or Looker)
- Understanding of crypto derivatives markets, margining, and funding-rate mechanics
- Experience working cross-functionally with Sales, Product, and Marketing teams
- Strong communication skills; able to translate data into actionable commercial insights