Hi! We have an opening for a ✈️ Middle Marketing Analyst ✈️ at an international startup.
🚨 But! We need people with experience in fintech, trading, iGaming, or other verticals with high CPA.
Client: International startup in CFD/Forex/Brokerage
Salary: up to $3000, paid in crypto
Location: Europe, CIS, excluding RF and RB.
Work format: full remote, flexible schedule, European time zone
Team: Russian-speaking
Responsibilities:
- Reporting on User Acquisition efficiency: analysis of expenses, CPA, ROAS, funnel from click to FTD, broken down by channels, campaigns, geographies, and partners.
- Reconciling data between ad accounts, AppsFlyer, and the corporate data warehouse, identifying and investigating discrepancies.
- Responsibility for setting up attribution and conversion postbacks in Facebook and Google ad accounts.
- Analysis of affiliate and partner traffic, monitoring source quality, and identifying problematic platforms.
- Defining data collection requirements: what fields and events need to be collected and from which sources.
- Investigating tracking issues: lost events, incorrect attribution, data duplication, spending anomalies.
- Regular interaction with the UA team: explaining current indicator dynamics, reasons for changes, and their impact on business metrics.
Requirements:
- 2+ years of experience in marketing or product analytics with a focus on User Acquisition.
- Proficient SQL: aggregations, window functions, independent work with raw data.
- Experience with MMP (AppsFlyer, Adjust, Branch): attribution, postbacks, deeplinks, understanding the differences between web and in-app tracking.
- Understanding of attribution models and their limitations, ability to explain discrepancies between ad account data and internal company data.
- Practical experience with Facebook and Google Ads at the data level: campaign structure, data exports, working with APIs.
- Experience analyzing User Acquisition unit economics: CPA, ROAS, cohort payback.
- Experience with BI tools: Power BI, Metabase, Tableau, or similar.
- Ability to independently find the root cause of data discrepancies, not just record and forward information about the problem.
