About the role

Monitor core conversion funnels and develop user tagging systems to identify optimization opportunities and predict churn. Create data dashboards and quantitative revenue models to evaluate marketing incrementality and business health.

What they look for

MySQL SQL Data Visualization User Segmentation Causal Inference Quantitative Modeling Event Tracking Churn Prediction Cohort Analysis Performance Tuning Tableau Power BI QuickBI Data Cleaning Business Acumen Conversion Funnel Analysis

Requirements

Requires a Bachelor's degree in a quantitative field and proficiency in complex MySQL querying and performance tuning. Candidates should have experience in user clustering, causal inference, and data visualization tools.

Full description

Job Title: User Data Analyst (Junior/Mid-Level)

Experience Required: 1-5 Years

Responsibilities:

Full-Funnel Conversion Monitoring & Drill-Down Analysis: Responsible for the daily monitoring and anomaly detection of the core conversion funnel (Registration -> KYC -> Deposit). Accurately identify drop-offs through dimensional breakdowns, event tracking analysis, and industry trend interpretation. Proactively discover optimization opportunities for deposit/withdrawal channel routing.

User Segmentation & Tagging System: Collaborate with the Data Warehouse team to build and maintain a comprehensive user tagging system based on trading behavior, activity levels, and lifecycle stages. Develop a churn prediction and early-warning metric system.

Marketing Campaign Incrementality Evaluation: Work closely with the Strategy Operations team to evaluate internal and external user acquisition and reactivation initiatives. Conduct longitudinal comparisons and cohort back-testing to accurately assess the pure incremental traffic and business value generated by various intervention strategies.

Core Data Dashboard Development: Independently conduct data source research, data cleaning, metric calculation, and dashboard creation using MySQL to support the team's daily monitoring and retrospective analysis.

Core Business Quantitative Modeling: Build revenue contribution models for various business lines to clarify the baseline health of each operation. Quantify the elastic impact of localized growth on the platform's overall revenue through sensitivity analysis of core metrics.

Qualifications:

Bachelor's degree or above, preferably in Statistics, Mathematics, Computer Science, or related fields.

Proficient in MySQL/SQL querying. Highly skilled in writing complex multi-table joins, aggregate functions, and window functions. Proven ability in performance tuning for queries involving tens of millions of high-frequency transaction records.

Solid mastery of user clustering and segmentation methods. Deep understanding of causal inference fundamentals and baseline selection for Before/After longitudinal experiments, with proven real-world implementation cases.

Hands-on experience with at least one mainstream data visualization tool (e.g., Tableau, Power BI, QuickBI).

Strong sense of ownership and structured business acumen. Ability to see through the essence of payment and growth operations via data, translating scattered insights into clear, actionable business strategy recommendations.

Preferred: Experience analyzing B2C products in Internet Finance, Global Payments, FinTech, or Web3. Background in user growth or user operations analysis is highly advantageous.

Bonus Points:

Experience in event tracking design and implementation (Data Tracking Architecture).