Job Description:
Data Analyst / BI Analyst
- Conduct data analysis for business areas such as transactions, assets, users, and advertising/growth, breaking down core metrics based on business objectives and providing optimization recommendations.
- Independently complete SQL data extraction, data verification, ad-hoc reports, periodic reports, and specialized analysis for product, operations, risk control, and finance teams.
- Develop core business indicator systems, including but not limited to transaction volume, turnover, active users, retention, conversion, asset scale, deposits/withdrawals, orders, user segmentation, and channel effectiveness.
- Build BI dashboards and automated reports, creating reusable data reports to improve self-service data access and decision-making efficiency for business teams.
- Participate in data warehouse modeling, collaborating with data developers to design dimension tables, fact tables, and DWD/DWS/ADS layer models, ensuring unified metrics, data quality validation, and model reusability.
- Monitor and analyze business data anomalies, assisting in establishing data alert mechanisms to promptly identify fluctuations, metric inconsistencies, and pipeline delays.
- Support specialized business analyses, including user behavior analysis, transaction path analysis, funnel conversion analysis, retention analysis, campaign effectiveness, channel quality, and risk control data analysis.
- Collaborate with product, R&D, operations, risk control, and finance teams to implement data requirements and ensure accuracy in metrics, reports, and analytical conclusions.
Job Requirements:
- Bachelor's degree or higher in Statistics, Mathematics, Computer Science, Information Management, Financial Engineering, Data Science, or related fields preferred.
- 2+ years of experience in data analysis, BI analysis, business analysis, or data warehouse analysis, with preference for candidates in internet, fintech, exchanges, advertising, growth, risk control, or payment industries.
- Proficient in SQL, capable of complex queries, association analysis, window functions, group aggregation, and retention/funnel/segmentation analysis.
- Familiar with common data warehouse modeling methods, including dimension tables, fact tables, metric definitions, layered modeling, wide-table construction, data lineage, and quality validation.
- Proficient in at least one BI tool (e.g., Tableau, PowerBI, QuickBI, Superset, Metabase, DataWind, FineBI) and able to independently build business dashboards.
- Experience with one or more data query/analysis environments such as Hive, ClickHouse, Doris, Presto, Spark SQL, or MySQL.
- Strong business acumen, able to design analytical approaches based on business problems rather than just data extraction.
- Excellent logical expression and documentation skills, capable of producing clear analysis reports, metric definitions, and data conclusions.
- Data-sensitive, responsible, and proactive in identifying data anomalies and business issues.
Bonus Points:
- Experience in exchange, securities, futures, contracts, spot trading, quantitative trading, wallets, payments, risk control, or advertising growth analytics.
- Familiarity with trading-related metrics such as turnover, orders, order books, fund accounts, deposits/withdrawals, fees, user trading behavior, API users, or market-making/copy-trading.
- Experience in data warehouse model design, especially for user, order, asset, transaction, deposit/withdrawal, channel, or campaign domains.
- Proficiency in Python for data cleaning, automated analysis, report generation, or anomaly detection.
- Experience in A/B testing, user segmentation, tagging systems, audience targeting, growth analysis, or risk control analysis.
- Knowledge of real-time data warehouses, Flink, Kafka, ClickHouse, Doris, or Paimon.
Benefits:
- Competitive global compensation and incentive mechanisms.
- A fast-paced work environment with top-tier industry teams.
- Flexible work arrangements and high autonomy.
- Core opportunities to contribute to global brand building.
