Sulu Yan
Manager, Sales Intelligence at Lennox
Dallas-Fort Worth Metroplex United States
Summary
🤩
Rockstar🎓
Top SchoolSulu Yan is a sales intelligence manager with a strong analytics and BI engineering background, blending three years of leadership at Lennox with over a decade of SAP and data warehouse experience. She progressed from pricing analyst and Qlik Sense developer to leading sales intelligence, driving ETL, data model optimization, and role-based authorization for enterprise reporting. Technically hands-on, she has contributed to open-source ML model serving work—integrating LLM pipelines and optimizing VLLM backends—bringing machine learning deployment insights to sales analytics. Her cross-functional experience spans SAP BW, Oracle, Informatica and Qlik, enabling her to translate complex data ecosystems into actionable commercial insights. Trained at Zhejiang University and UT Dallas in e-business and business intelligence, she combines international systems implementation know-how with modern ML-informed analytics leadership.
3 years of coding experience
6 years of employment as a software developer
Master of Science in Information & Technology and Management Enterprise Systems/Business Intelligence and Analytics, Master of Science in Information & Technology and Management Enterprise Systems/Business Intelligence and Analytics at The University of Texas at DallasBachelor E-Business, Bachelor E-Business at Zhejiang University
Github Skills (15)
machine-learning10
deeplearning-ai10
nlp10
deep-learning10
python10
llm10
pytorch9
docker8
github-ci8
transformers8
cicd8
dockers8
githubaction-workflow8
test-automation7
computer-vision4
Programming languages (3)
Github contributions (5)
modelscope/modelscope
Nov 2022 - Mar 2025
ModelScope: bring the notion of Model-as-a-Service to life.
Role in this project:
ML Engineer & DevOps Engineer
ML Engineer & DevOps EngineerContributions:1 release, 14 reviews, 51 PRs in 2 years 5 months
Contributions summary:Sulu primarily focused on the ModelScope project's integration of different machine learning models and frameworks, and in particular, on LLM pipelines. They worked on setting up the VLLM backend for language models, including configuration and default settings, optimizing parameters for different models. Additionally, the user made improvements to the codebase, added and fixed templates, and addressed dependencies related to model serving. The user also addressed issues in testing frameworks related to plugins.
nlppytorchmulti-modalpythonscience
suluyana/modelscope-agent
Nov 2023 - Jan 2024
ModelScope-Agent: An agent framework connecting models in ModelScope with the world
Contributions:49 pushes, 14 branches, 1 tag in 1 month
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