Worldquant19d ago

Data Engineer

Ho Chi Minh Citymid

Data EngineeringData EngineerDataData & AI

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Quick Summary

Key Responsibilities

Enriching a wide range of structured and unstructured data into datasets for quantitative analysis and financial engineering.

Technical Tools

Data EngineeringData EngineerDataData & AI

WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform.

WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement.

Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it.

Responsibilities

~1 min read

→Strong academic background – minimum of a bachelor’s degree in a technical or quantitative field.
→Practical experience with and understanding of deep neural networks and other machine learning techniques.
→Demonstrated ability to implement data science pipelines and real-time applications in Python
→3+ years of relevant experience as a Data Engineer or similar roles.
→Proficiency with python-based tools like Jupyter notebook, coding standards like pep8.
→Experience with LLM/AI for data processing is a plus
→Exceptional analytical & problem-solving abilities, with a strong attention to detail.
→Good command of English
→Excellent software development skills: ability to convert rough overall use-cases to a working codebase.\
→Motivated by a deep curiosity and passion to learn is a plus.
→Past experience as a data scientist or data engineer in finance or investment profile is a plus.
→Experience with Linux/Unix shell and Git is a plus.