Data Engineer

Posted 16 Hours Ago
Be an Early Applicant
2 Locations
Junior
Financial Services
The Role
The Data Engineer will design, implement, test, deploy, and monitor production data pipelines using MLOps. The role requires collaboration with teams to produce scalable and fault-tolerant data systems, employing best coding practices and focusing on machine learning and Large Language Models (LLM).
Summary Generated by Built In

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: The Data Engineer plays a pivotal role in the development of our data systems. A successful candidate will design, implement, test, deploy, and monitor production data pipelines using MLOps methodology in close collaboration with other teams. The candidate will need to quickly learn and apply new cutting-edge technologies, focusing on Large Language Models (LLM). The goal is to produce agile, scalable, and fault-tolerant systems as we grow in size and sophistication. This person will follow coding best practices, participate in code and design reviews, and advocate for coding excellence.

What You’ll Bring:

  • Degree in a quantitative or technical discipline (computer science, engineering, etc.)
  • At least 2 years’ experience in developing and managing scalable and robust data pipelines
  • Have a deep understanding of machine learning and experience in training, inference, and evaluation.
  • Excellent Python coding skills; familiarity with pandas & Spark is required
  • Strong analytical skills and attention to detail
  • Excellent communication skills in both verbal and written form
  • Ability to operate in a collaborative, team-oriented culture
  • Proactive and mature approach to problem-solving and project management
  • Experience with Kubernetes (k8s) for deployment is preferred 
  • Experience with monitoring and alerting tools is preferred 
  • Experience with LLM technologies (OpenAI-compatible, llama.cpp, vllm) is preferred 
  • Familiarity with infrastructure management and deployment and ML Ops is preferred 


What We Offer:

  • Competitive and attractive compensation package with clear career road-map – where you feel challenged everyday
  • We offer a strong culture of learning and development: training courses, library, speakers, share and learn events
  • Learn from who sits next to you! Working in WQ you are surrounded by smart and talented people
  • Employee resources groups with strong diversity and inclusion culture
  • Premium Health Insurance and Employee Assistance Program
  • Generous time-off policy, re-creation sabbatical leave (based on tenure), Trade Union benefits for staff and family
  • Team building activities every month: Local engagement events, monthly team lunch – Employee clubs: football, ping-pong, badminton, yoga, running, PS5, movies, etc.
  • Annual company trip and occasional global conferences – opportunity to travel and connect with our global teams
  • Happy-hour with tea break, snacks and meals every day in the office!

#LI-NV1

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.

Copyright © 2024 WorldQuant, LLC. All Rights Reserved.
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.

Top Skills

Python
The Company
HQ: Old Greenwich, CT
2,008 Employees
On-site Workplace
Year Founded: 2007

What We Do

WorldQuant is a global quantitative asset management firm with over $7 billion in assets under management. Founded in 2007 by Igor Tulchinsky with the belief that talent is global, but opportunity is not, WorldQuant has more than 1,000 employees spread among 26 global offices. WorldQuant seeks to get to the future faster, guided by the principle that there are an infinite number of insights to discover. The firm develops and deploys investment strategies across a variety of asset classes in global markets. For more information on WorldQuant’s philosophy and culture, please visit www.worldquant.com.

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