Data Engineer (7673)

TSMC•San Jose, CA

5d•Onsite

About The Position

Collect, process, and manage data, facilitating further interpretation of the model created by data scientists. Create, construct, and maintain the essential infrastructure for storing and processing vast amounts of data. Collaborate closely with data scientists to ensure that the data is correctly organized and available for analysis. Develop data pipelines for data scientists to extract insights from structured and unstructured data using AI-enabled analytics procedures. Work with Big Data technologies, NoSQL databases, machine learning and deep learning algorithms to capture profitable growth opportunities and future challenges. Analyze intricate product and platform usage patterns, translating data-driven insights into actionable product strategy and engineering decisions. Deploy automated solutions, ranging from data automation to real-time Python classification and ML modeling and user interfaces, to address key issues. Conduct data analysis, statistical modeling, machine learning modeling, and data visualization. Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or models.

Requirements

Master’s degree or foreign equivalent in Computer Science, Information Systems, Applied Data Science, Development Engineering or related field, and 6 months of experience in a related position
Knowledge of Python (with Jupyter, PyCharm, or similar environment), GitHub, and Markdown
Knowledge on how to extract content (e.g., with regular expressions, entity extraction) from unstructured data and format the extractions into data structures such as lists, trees, graphs, grids, and/or sequences
Knowledge of conventional machine learning and deep learning algorithms and packages, including scikit-learn, Keras, and/or Pytorch
Knowledge of relational data management, including extracting, transforming, loading, querying from MySQL databases
Experience connecting to REST API endpoints, particularly in parsing data in JSON and XML formats
Experience developing and deploying machine learning and deep learning pipelines and development and deployment of front-end/UI systems including Streamlit, Dash, and ReactJS
Experience in finance, accounting, and market analysis
Experience with NLP data extraction and modeling using techniques, including named entity recognition, sentiment analysis, topic modeling using SpaCy, NLTK, and Hugging Face Transformers
Experience developing and deploying machine learning models for image based model and robotic applications, including image preprocessing with OpenCV and optimizing convolutional neural

Responsibilities

Collect, process, and manage data
Create, construct, and maintain the essential infrastructure for storing and processing vast amounts of data
Collaborate closely with data scientists to ensure that the data is correctly organized and available for analysis
Develop data pipelines for data scientists to extract insights from structured and unstructured data using AI-enabled analytics procedures
Work with Big Data technologies, NoSQL databases, machine learning and deep learning algorithms to capture profitable growth opportunities and future challenges
Analyze intricate product and platform usage patterns, translating data-driven insights into actionable product strategy and engineering decisions
Deploy automated solutions, ranging from data automation to real-time Python classification and ML modeling and user interfaces, to address key issues
Conduct data analysis, statistical modeling, machine learning modeling, and data visualization
Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer
Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or models