Lyufa Z.

Key Skills

Software

Other

Top Subject Matter

Financial services data validation and predictive modeling

FinTech customer segmentation and cohort analytics

Market research analytics and predictive modeling

Top Data Types

Document

Text

Top Task Types

Data Collection

Freelancer Overview

Managing Data Specialist (Data Scientist) — Capgemini (China) Co., Ltd. for Daimler Financial Services / Mercedes-Benz. Brings 12+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Master of Science, Lancaster University (2014) and Marketing (Exchange Student), University of the West of England, Bristol (2013). AI-training focus includes data types such as Document, Computer Code, and Programming and labeling workflows including Data Collection.

Labeling Experience

Managing Data Specialist (Data Scientist) — Capgemini (China) Co., Ltd. for Daimler Financial Services / Mercedes-Benz

OtherDocumentData Collection

Worked as Managing Data Specialist (Data Scientist) delivering data science solutions for Daimler Financial Services/Mercedes-Benz, including client-facing analysis validation. While the role focused on modeling and validation, it included preparing and validating datasets used for downstream predictions and reporting. This involved extracting and cleaning data and ensuring integrity before analytical and experimentation workflows. • Performed data validation via SQL and built reconciliation reports to ensure correctness across 10M+ records. • Conducted data extraction, transformation, outlier handling, and imputation using SQL and Python. • Built Logistic Regression and Random Forest models for customer loan conversion prediction. • Supported A/B test validation and responded to ad-hoc client analysis requests (e.g., early termination and contract restructuring).

2017 - 2020

Data Analyst — Shanghai PaiPai Dai Financial Information Service Co., Ltd. (FinTech)

OtherData Collection

Served as a Data Analyst in a FinTech context using segmentation and cohort analysis to drive targeted customer messaging and retention measurement. The work relied on dataset preparation and analytics rather than manual annotation. It supported marketing personalization decisions based on derived labels such as customer segments and retention cohorts. • Used K-means clustering in R to segment customers and identify high-value groups for targeted SMS/text campaigns. • Collaborated with marketing teams to operationalize segment-based messaging strategies. • Performed SQL-based cohort analysis across acquisition channels to track user retention. • Identified underperforming channels and recommended strategy adjustments based on measured retention outcomes.

2016 - 2016

Data Analytics Consultant — Nielsen Market Research (for P&G, Wyeth, Starbucks)

OtherDocumentData Collection

Worked as a Data Analytics Consultant for FMCG clients, translating multi-city and multi-segment market data into predictive insights. The role involved building statistical models and generating structured reporting outputs used by stakeholders for decision-making. While not an annotation role, it produced labeled insights such as category priority matrices and high-propensity customer predictions. • Built regression models in SPSS to predict sales across categories and cities, then created a city-category priority matrix. • Developed logistic propensity models in R to identify likely Starbucks customers and validate campaign lift. • Led monthly market share tracking across segments and competitors using SAS and synthesized findings into reports. • Presented results to senior stakeholders, influencing channel expansion and marketing budget allocation decisions.

2015 - 2016

Education

Work History