Xuhui District, Shanghai, China
5+ years of experience at multinational FMCG companies, specializing in analyzing sales performance, consumer research, and product evaluation data. Expert in generating segmented insights through rigorous data analysis, with hands-on expertise in SQL, Python, Tableau, and Power BI. Self-driven in translating complex data into actionable business insights, with strong learning agility and fluent professional English. I get excited about opportunities where I'm able to leverage big data to discover insights and identify opportunities that provide real consumer impact. I love connecting with new people, give me a shout at [email protected] or here on LinkedIn!
R&D | Beauty & Well-being (Skincare) | Consumer Insight • Quantitative research: Analyzed quantitative consumer preference/benefit agreement data from product usage, delivering segmented insights by skin type, skin tone, age, and other demographics to identify key preference differences and support business decision-making. • Qualitative research: Leverage qualitative methods such as FGD/1v1 interview to understand consumer usage behavior such as perception of brightening benefit during cream usage • Product Analysis: Developed an automated Python workflow for data extraction and cleaning, PCA, and statistical significance testing, producing pairwise comparison visualizations to quantify performance gaps versus previous prototypes and competitor products, supporting formulation decisions. • Predictive model: Built a predictive model by linking R&D indicators with quantitative consumer preference; aligned metric definitions and modeling logic with external partners, continuously optimized model performance, and validated outcomes through real-world consumer tests.
Product Performance Evaluation | R&D • Product Positioning: Applied feature quantile analysis to establish competitive product positioning, clearly defining relative standing within the category and providing data-driven support for product positioning and formulation upgrades. • Category Analysis: Performed systematic analysis of category-level R&D data using multivariate methods such as Principal Component Analysis (PCA) and cluster analysis. Assessed differences across countries, price tiers, and performance dimensions to clarify category structure and competitive landscapes
South Regional Distributor Development | Sales • Promotion Campaign Analytics: analyzed promotion campaign data; calculated key business KPIs (e.g., order volume, GMV/revenue, average order value, active merchants), tracked growth versus prior periods, regional and individual target attainment, and sales rep rankings; delivered daily/weekly/monthly reports to provide stakeholders with timely, clear visibility into sales performance. • Efficiency Improvement: Standardized reporting through Excel templates with embedded formulas, enabling plug-and-refresh updates to improve accuracy and increase efficiency by 50%.