Jingjie Z.

Key Skills

Software

No software listed

Top Subject Matter

Materials science / experimental characterization (flame-retardant MXene-based thermoelectric materials)

Educational AI / language learning analytics (vocabulary retention)

Top Data Types

Document

Text

Top Task Types

Data Collection

Tracking

Freelancer Overview

Experimental Data Analyst | Huaqiao University (MXene-based flame retardant thermoelectric materials study). Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Origin and VS Code. Education includes Bachelor of Materials Science and Engineering, Huaqiao University (2026). AI-training focus includes data types such as Document and Text and labeling workflows including Data Collection and Tracking.

Labeling Experience

Educational Software Developer & Data Manager | Sagepath (anti-forgetting vocabulary retention tracking system)

TextTracking

Designed and implemented an anti-forgetting review algorithm to strictly track and manage user vocabulary retention data. Required precise data structuring and database management to ensure accurate user metrics and reliable learning triggers. Continuously analyzed user learning data to optimize system performance and maintain correctness of data-driven behavior. • Tracked vocabulary retention over a 21-day Ebbinghaus cycle • Structured and stored user learning progression metrics in a database • Calibrated algorithmic triggers based on user retention data • Conducted ongoing analysis of learning data to validate system behavior

Not specified

Experimental Data Analyst | Huaqiao University (MXene-based flame retardant thermoelectric materials study)

DocumentData Collection

Processed and annotated large volumes of experimental datasets from sensitive laboratory equipment for subsequent analysis and reporting. Ensured structured, zero-error documentation of measured material performance metrics to support accurate academic evaluation. Maintained a rigorous workflow for cleaning, categorizing, and preparing data outputs suitable for downstream modeling or review. • Annotated experimental measurement outputs (SEM, XRD, TEM, DSC) • Cleaned and organized complex datasets for visualization and analysis • Produced documentation of material performance metrics with high precision • Used Origin for data cleaning, categorization, and visualization

Not specified

Education

Work History