Ted_Zhao_ML.yaml

cv:
  name: Ted Zhao
  location: 10/4 Sheppards Lane, Norwood SA 5067, Australia
  email: ted.zhao.au@gmail.com
  phone: "+61-416-551-622"
  social_networks:
    - network: LinkedIn
      username: ted-zhao
    - network: GitHub
      username: tade0726
  sections:
    summary:
      - bullet: Machine Learning Engineer with 5+ years of experience delivering end-to-end AI solutions across fintech, travel, and retail sectors.
      - bullet: Expertise in RAG systems, computer vision, and reinforcement learning, improving business metrics by 2-10% across projects.
      - bullet: Strong MLOps background with Databricks, MLflow, and ZenML, focusing on production-grade model deployment and monitoring.
      - bullet: Track record of innovative solutions from credit scoring to LLM-powered chatbots, consistently driving business value through AI.
    experience:
      - company: Rainmakr.ai
        position: Data/AI Engineer
        location: Adelaide, SA (Remote)
        start_date: 2023-05
        end_date: 2024-07
        highlights:
          - Developed LLM prompts with RAG to categorise company data into GICS-like themes, enhancing industry analysis.
          - Built knowledge graphs from LLMs to extract entity relationships (executives, competitors, supply chains) for financial insights.
          - Simplified 30+ table data models with DBT, reducing schema size by 50% and redundant data by 15%.
          - Optimised queries through join refinement and re-indexing, cutting runtime by 50%.
          - Integrated DBT with Dagster Cloud for mixed orchestration of notebook and DBT jobs.
      - company: Skyscanner
        position: ML Engineer/Data Scientist
        location: Shenzhen, China
        start_date: 2019-11
        end_date: 2021-07
        highlights:
          - Led end-to-end ML pipeline in Databricks/MLflow, engineering user behaviour features and iteratively improving CTR by 5-10%.
          - Deployed ensemble of LightGBM and Deep Learning models with A/B testing framework for continuous model refinement.
          - Developed ResNet-based classifier for 20 hotel categories with hierarchical labelling system, achieving 99% Top-5 accuracy.
          - Enhanced image selection using MobileNet with multi-dimensional aesthetic scoring (composition, lighting, detail), lifting CTR by 3%.
          - Built T+1 batch processing pipeline using AWS Lambda/PySpark for feature extraction, storing in Parquet format.
          - Engineered real-time feature streaming from Elasticsearch with Redis caching, improving inference CTR by 2%.
      - company: DJI
        position: Data Scientist
        location: Shenzhen, China
        start_date: 2018-04
        end_date: 2018-08
        highlights:
          - Built Scrapy-based web crawler to gather city demographics and competitor store distribution data for market analysis.
          - Developed quantitative ranking algorithm incorporating economic indicators and business factors for city prioritisation.
          - Analysed post-launch user demographics (location, income, age) to create detailed customer segments.
          - Monitored sales patterns and provided data-driven insights for campaign strategy optimisation.
          - Developed Django/SQLAlchemy-based API for Jupyter extension, enabling efficient SQL querying and data model management.
      - company: Smart Decision Technology Ltd
        position: Data Scientist
        location: Shenzhen, China
        start_date: 2015-08
        end_date: 2018-03
        highlights:
          - Implemented credit scorecard system with feature selection, WOE calculation, and logistic model conversion in Python.
          - Built SimPy-based logistics simulation with Flask/SQLAlchemy backend, securing 2-year contract with S.F. Express.
          - Applied K-Means clustering for HKJC member segmentation, delivering lifecycle-based targeting strategies.
          - Developed Chinese text sentiment analysis using Word2Vec and K-means for thematic clustering.
          - Built supervised learning model with custom Chinese tokenization for app review classification.

    projects:
      - name: ATO Chatbot
        date: 2023
        highlights:
          - "**Live Demo**: [ato-chat.streamlit.app](https://ato-chat.streamlit.app/) | **Source**: [github.com/tade0726/ato_chatbot](https://github.com/tade0726/ato_chatbot)"
          - Built production-grade RAG system with LlamaIndex and Qdrant vector store, enabling context-aware tax information retrieval.
          - Implemented MLOps pipeline with ZenML for data ingestion, OpenAI fine-tuning, and automated model evaluation.
          - Developed Streamlit-based UI with real-time query rephrasing and source citations for enhanced user trust.
      - name: Quantitative Trading with Reinforcement Learning
        location: University of Adelaide
        date: 2022-09
        end_date: 2023-02
        highlights:
          - Researched and developed crypto trading strategy using Reinforcement Learning at University of Adelaide.
          - Designed multi-asset portfolio optimisation with Sharpe Ratio reward system for buy/sell quantity decisions.
          - Built dual Deep Learning modules for price signal prediction and market sentiment analysis.
          - Implemented comprehensive backtesting framework evaluating Sharpe Ratio and Maximum Drawdown (MDD).
          - Developed profit analysis system incorporating trading fees and compound returns visualisation.
    
    skills:
      - label: ML/AI
        details: Reinforcement Learning, Deep Learning, Clustering, LightGBM, XGBoost, SVM, Word2Vec, A/B Testing
      - label: MLOps/Cloud
        details: Azure ML, AWS, SageMaker, MLflow
      - label: Data Engineering
        details: DBT, Databricks, Snowflake, Dagster
      - label: Programming
        details: Python, VBA, Scala, Julia
      - label: Web Development
        details: Django, Flask, Asyncio, Scrapy
      - label: ETL/Data Tools
        details: SQL, SQLAlchemy, Spark, Pandas, Tableau
      - label: Version Control & Containers
        details: Git, Docker
    education:
      - institution: University of Adelaide
        area: Machine Learning
        degree: Master
        location: Adelaide, SA
        start_date: 2021-06
        end_date: 2023-05
      - institution: Shenzhen University
        area: Mathematical Sciences
        degree: Bachelor
        location: Shenzhen, China
        start_date: 2010-09
        end_date: 2014-07
    languages: 
      - "**English**: IELTS 7.0 **Mandarin**: Native **Cantonese**: Native"
    certifications:
      - area: Machine Learning - https://www.coursera.org/account/accomplishments/verify/Q89DMB9RYYTB
        institution: Coursera
        date: 2016-10
      - area: Machine Learning Nanodegree - https://graduation.udacity.com/confirm/PKAQPLU2
        institution: Udacity
        date: 2018-12
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rendercv_settings:
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