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宋浩茹 Hao-Ru Sung| [email protected] | LinkedIn ｜ GitHub A s a Research Assistant at Academia Sinica , specializing in Generative AI research and application. With 3 + years of experience in NLP a nd Machine Learning , along with 4+ years in Backend Development . Proficient at translating complex theories into practical applications. Skills Languages: Python, R, SQL, MATLAB, C, C#, JavaScript, Node.js Software & Tools: PyTorch, PyTorch Lightning, Tensorflow, Scikit-Learn, NLTK , GCP, Linux, SQL / NoSQ , Pandas, Hugging Face, Gradio, LangChain, Tensorflow, Keras, FastAPI, OpenCV, Airflow

Data Scientist Intern @ Cathay Financial Holdings. 國泰金控 Digital data & Technology (DDT, 數數發) Research into Interpretable Machine Learning and its existing algorithms. Experimented LIME & SHAP on open data. ( GitHub ) Real Estate Evaluation model – Geographical/Credit Card data gathering, cleaning, feature engineering (Hit-rate performance improved from 55% to 70%) Python Machine learning Data Pipelines Web Crawlers PyTorch, Airflow, Pandas, docker SQL Extract-Transform-Load(ETL) Efficiency(Window Functions) Language Chinese(Native) English (TOEIC 905/990 TOEFL 96/120) Project(@ Esun only) ( Powerpoint demo link, clic...

with reliable data, and saved 50% effort (Groovy, Dataproc, Spark, BigQuery, EMR, Hive, Jenkins) • Designed ETL pipeline framework and implemented it to cloud service and held user training sessions for engineers and analysts. This project was reduced by 40% maintenance efforts and increased by 60% deployment efficiency by leveraging Airflow and Kubernetes (Gitlab, Airflow, Python, K8s) Developed and deployed API to retrieve data in the cloud environment • Developed an API to retrieve data that included geo-location data from BigQuery and deployed it on the GCP environment. The API saved 80% of the time on fetching data (Cloud

import traditional CSV files. Utilized Databricks for large-scale data processing, leveraging its Spark capabilities to efficiently transform and aggregate incoming data streams. With the combined power of Databricks and AWS Lambda, ensured unparalleled data consistency, quality, and preparedness for sophisticated analytics and reporting. Utilized Databricks and Airflow to run extensive data profiling tasks, analyzing data patterns and identifying potential quality issues before they reached the Databricks Delta Lake. Established robust guardrails using the combined might of AWS Lambda, Apache Airflow and Databricks, ensuring that data stored in the DataBricks Delta Lake consistently met the highest

估等數據與機器學習的問題變得有趣的問題。 目前關注學習目標 nodejs、go、GCP、dataOps/MLOps、k8s/docker、ansible/cobbler(配置管理)、jenkins/gitlab-ci(ci/cd)、airflow、mlflow、nginx、redmine/testlink(需求與issume管理)、git/dvc(版本管理)、Scikit-learning/TensorFlow(機器學習/深度學習) ▲豐富的軟體產品與專案開發▲ 豐富且多

/ ETL / BPM 各系統開發&維運人員) Power BI (Power BI / SSAS / SSRS / Paginated Report) RPA 自動化(Automation Anywhere / Power Automate / Power Automate Desktop) Power Platform ( Power Automate / Power Apps / Power BI) ETL (Nifi / Airflow / Kettle / DataStage) Business Process Management (BPM System) Data Engineer ( 協助數據串接 / 數據分析 / 報表製作 / 流程自動化) 配合User 單位，協助各系統專案導入 Columbus 使

workers which off-line scooter should be exchanged battery first. • Built LSTM model to forecast rental demand through user app events understanding the fulfill rate of every operational region. • Assessed parking lot value, consulted which one should be deprecated, where could develop new parking lot service. • Applied Airflow to ensure the stability and accuracy of data. Data Engineer • Breaktime INC. 四月十月 2019 • Crawled articles from different webs and constructed NLP model integrated text-CNN, Logistic, LightGBM, accuracy around 91%. • Analyzed content of articles to calculate content similarity, then recommended readers related