Google NotebookLM Over My Resume

I uploaded my resume to notebooklm.goo... and generated an audio overview.
Briefing Doc: Lily Su - Business Intelligence Engineer
This briefing doc summarizes the key skills, experience, and projects undertaken by Lily Su, based on her provided resume.
Summary:
Lily Su is an experienced Data Scientist and Machine Learning Engineer with a proven track record of working with large-scale data infrastructures. Her experience spans across various industries, including finance, telecommunications, and technology, where she has successfully applied data science techniques to solve complex business problems.
Key Skills:
Technical Skills: Python, SQL, Snowflake, Microsoft SQL Server, Data Analysis, Data Science, AWS, LLMs, Confluence, Jupyter, Business Analytics, Git, Microsoft Azure, NumPy, Pandas, Pytorch, Tensorflow, Kubernetes, Excel/Numbers/Sheets, Agile, Azure Synapse, PySpark Databricks, Docker, FastAPI, JIRA, ServiceNow, Selenium, SCRUM, SAP Products, Salesforce, PowerPoint/Keynote/Slides, Postgres, Oracle, Linux/Unix, Databases, Data Modeling, Data Engineering, Java
Domain Expertise: Data Science, Machine Learning, LLM's, NLP, HPC, Distributed Computing, Underwriting, Data Pipelines, ETL, Dashboarding, Model Explainability, Data Visualization, Business Intelligence, Cloud Computing
Notable Experience:
LLM-focused Data Engineering: At MultiOn, Lily develops data pipelines and dashboards to analyze user behavior and evaluate LLM performance. This includes extracting data from various sources, transforming it using Python Pandas, and visualizing it through Grafana and Mixpanel. She highlights her role in "Guided the overall design as well as data pipeline infrastructure for implementation of dashboarding over LLM evaluation metrics for model explanatory and model performance purposes."
Machine Learning for Underwriting: At Discover Financial Services, Lily leveraged machine learning techniques to improve underwriting processes for consumer credit card applications. This involved analyzing the business impact of underwriting changes, ensuring data quality, and investigating data discrepancies. She states her key contribution as "Investigating, reporting findings, and advocating for absolute parity between legacy and modern systems on customer credit card application data."
Building Data-Driven Solutions: At T-Mobile, she led the development of a self-service data product for the procurement organization, enabling data-driven decision-making. Lily was instrumental in "Synthesized un-documented data to determine its value and translate it into business metrics KPIs."
Client-Facing Data Science Consulting: At Data Analytics NYC, Lily collaborated with clients to build data pipelines and apply data science methodologies to large datasets. She developed models for various domains, including finance, marketing, and e-commerce. Her work at Predicio, where she "Set up a data pipeline system to process a data lake of live streams of telematic data using PySpark and Jupyter Notebook," showcases her expertise in handling real-time data.
Overall Impression:
Lily Su possesses a strong combination of technical expertise and business acumen. Her experience demonstrates a consistent ability to understand business needs, translate them into technical solutions, and deliver impactful results. Her passion for data science and emerging technologies, particularly LLMs, makes her a valuable asset in today's data-driven world.
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