Skills & Experience

This page summarises my core skills as a data analyst and my experience across finance, telecom, local services and content safety.

Core Technical Skills

Over years of working with data, I have developed a stable toolkit around data collection, modeling, analysis and communication to support product and business decisions.

Python data analysis: comfortable with pandas / numpy for data cleaning, feature creation and metric calculation.
SQL and data extraction: able to work with complex schemas to join, aggregate and prepare analysis datasets.
Metric system & data modeling: design metric systems and topic-wide tables aligned with business goals.
Basic machine learning: experience in participating in classification / prediction projects with feature engineering and evaluation.
Data visualization: building dashboards or custom visualisations to communicate findings to stakeholders.
Problem decomposition & storytelling: translate business questions into measurable metrics and analysis plans.

Project-Specific Skills & Domain Experience

Through real projects in different industries, I have built up an understanding of domain metrics, risk logic and operational strategies that can be transferred to new products and analysis tasks.

Finance & accounting basics: understand core concepts like balance sheet, P&L and cashflow to support modeling and KPIs.
Financial risk and credit: experience in risk rule analysis and scorecard-related work, focusing on delinquency and default metrics.
Telecom operator data: user lifecycle analysis, plan strategy evaluation and campaign performance measurement.
Local services (to-store & to-home): build merchant, order and traffic dashboards and analysis frameworks.
Content safety: participate in policy and model performance analysis with attention to recall and false positive trade-offs.
Data modeling & data product collaboration: hands-on collaboration with data warehouse and tracking design.