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yimin Lin

@yiminlin

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Data Analytics Lead and Data Engineer focused on BI, ML, and LLM-driven automation.

China

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What I'm looking for

I’m looking for a role where I can build and improve BI/data systems, strengthen analytics (segmentation, LTV, tracking), and apply ML/LLMs to drive measurable decision impact, while collaborating closely across product, engineering, and business stakeholders.

I’m a Data Analytics Lead and Data Engineer who builds decision-ready data systems—from BI dashboards to event tracking and unified data platforms. At Pupu Technology, I built the department’s data system from scratch, improving decision-making efficiency by 20% through a user operations metric framework and BI platform.

I’ve also led lifecycle value modeling with Random Forest and rebuilt event tracking to raise event recognition accuracy from 85% to 97%. In my current independent AI applications work, I lead an automated long-form novel generation workflow with LLMs—optimizing prompt orchestration to cut inconsistencies and boost generation efficiency by ~40% through iterative evaluation.

Experience

Work history, roles, and key accomplishments

Current

AI Applications Project Lead

Current

Independent Project

Apr 2024 - Present (2 years 2 months)

Designed and implemented an automated long-form novel generation workflow using LLMs, from topic setting to final integration. Optimized prompts and orchestration to reduce inconsistencies and boost generation efficiency by ~40%, and ran iterative evaluations to validate controllability and limitations.

LLM Prompt Engineering Orchestration LLM Evaluation Workflow Automation Python Quality Consistency Optimization

Data Analytics Lead

Pupu Technology Co., Ltd.

Jun 2020 - Apr 2024 (3 years 10 months)

Built the department’s data system from scratch, including a user operations metric framework and BI platform, improving decision-making efficiency by 20%. Led lifecycle value modeling with Random Forest (raising LTV by 5%) and rebuilt event tracking to increase event recognition accuracy from 85% to 97%.

Random Forest LTV Modeling Event Tracking SQL Data & Analytics

Data Engineer

Meitu Technology Co., Ltd.

Dec 2017 - Apr 2019 (1 year 4 months)

Supported deep learning projects (e.g., face recognition) in collaboration with researchers, improving model accuracy by 10%. Collected and cleaned large-scale image datasets with Python and built a unified data management platform to standardize formats and reduce redundancy, including work on a patent for image annotation methods.

Deep Learning Data Support Python Data Management Image Annotation Data Standardization