- Location
- New Delhi · New Delhi, Delhi, India
- Department
- Research Division
- Source
- Greenhouse
Description
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.
The Role: We are seeking a candidate to join our team as a Data Engineer. The Data Engineer will partner with our close-knit team of quantitative researchers, technologists and data sourcing colleagues to analyze and enrich a broad range of structured and unstructured large-scale data.
Job responsibilities include, but not limited to the followings:
- Enriching a wide range of structured and unstructured data into datasets for quantitative analysis and financial engineering.
- Enhancing data quality & integrity by developing validation tools to measure the effectiveness of data enrichment.
- Becoming a domain expert on different deep learning and machine earning applications, analyzing & understanding the underlying dynamics and behaviors within the data.
- Develop insights based on the data and collaborate with the research team to generate signals.
- Developing the utility tools that can further automate the software development, testing and deployment workflow.
What You’ll Bring:
- 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.
By submitting this application, you acknowledge and consent to terms of the WorldQuant Privacy Policy. The privacy policy offers an explanation of how and why your data will be collected, how it will be used and disclosed, how it will be retained and secured, and what legal rights are associated with that data (including the rights of access, correction, and deletion). The policy also describes legal and contractual limitations on these rights. The specific rights and obligations of individuals living and working in different areas may vary by jurisdiction.
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WorldQuant is an equal opportunity employer and does not discriminate in hiring on the basis of race, color, creed, religion, sex, sexual orientation or preference, age, marital status, citizenship, national origin, disability, military status, genetic predisposition or carrier status, or any other protected characteristic as established by applicable law.
