---
title: 'Data Scientist at WorldQuant'
canonical: 'https://feeny.ai/job/data-scientist-worldquant-delhi-6mdhv4jzd2qv'
type: 'job'
last_seen: '2026-09-15'
---

# Data Scientist at WorldQuant

- **Company:** WorldQuant
- **Location:** Delhi, India
- **Posted:** 2026-09-10
- **Last confirmed live:** 2026-09-15
- **Apply:** https://job-boards.greenhouse.io/worldquant/jobs/4703128006

## Job 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: This is a highly unique opportunity for a Data Scientist to join a new and rapidly growing intraday team. In this role you will partner with our close-knit team of quantitative researchers, data engineers, technologists and data sourcing colleagues to research, engineer, and validate quantitative signals derived from high-frequency equity market data across multiple global markets, while owning the full lifecycle of a signal, forming a hypothesis about what market behavior predicts, engineering it into a feature, validating it with data, and shipping it into a production research platform. This is a research-focused data science role with meaningful hands-on coding and implementing signals within our internal framework.

Key responsibilities include:

- Research and engineer features from raw, high-frequency market data, translating market behavior hypotheses into quantitative signals.
- Implement signals within our internal simulation/backtesting framework, iterating between exploratory data analysis and framework-based implementation.
- Validate features through backtesting across historical data, checking behavior across different markets, regimes, and edge cases (e.g., market open/close, low-liquidity periods).
- Collaborate with research and engineering teams to align on implementation approaches, validation standards, and research decisions.
- Explore new and existing data sources to identify candidate signals worth developing further.
- Becoming a domain expert on different deep learning and machine learning applications for high frequency data, analyzing & understanding the underlying dynamics, market microstructure and behaviors within the data.
- Develop insights based on the data and collaborate with the research team to generate tradable
- 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.
- Strong data science background, with experience turning noisy, real-world data into validated, well-behaved signals or models.
- Rigorous quantitative programming skills, with the discipline to write accurate, production-quality, and performance aware code, including low-latency implementations where needed. Prior experience with C++ is a plus.
- Working knowledge of financial markets and how trading/market data behaves, or strong aptitude to learn it quickly. Prior market microstructure knowledge and experience with dark pools, trading and exchange data is a plus.
- Practical experience with and theoretical understanding of deep neural networks and other machine learning techniques in high frequency domain is a plus.
- Comfortably making pragmatic modeling tradeoffs under ambiguity while clearly articulating the reasoning behind them with data.
- Exceptional analytical & problem-solving abilities, with a strong attention to detail.

By submitting this application, you acknowledge and consent to terms of the [WorldQuant Privacy Policy.](https://www.worldquant.com/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 © 2025 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.

## About WorldQuant

## Company Overview
- **One-liner**: A global quantitative asset management firm that develops and deploys systematic investment strategies across asset classes using data, technology, and a global talent network.
- **Entity Type**: Private (bootstrapped – no external funding rounds disclosed)
- **Headquarters**: Old Greenwich, Connecticut, USA (primary hub among 28 global offices)
- **Founded**: 2007
- **Founders**: Igor Tulchinsky

## Core Business
- **Primary industry/industries**: Quantitative asset management, financial services, data science, artificial intelligence
- **Target customers**: Institutional investors (B2B); also serves individual contributors through its BRAIN platform and educational initiatives
- **Mission or purpose statement**: “Leverage data, talent and prediction to tackle complex challenges beyond financial markets” (from founder’s statement)

## Products & Services
- **Systematic Investment Strategies**: Core business – proprietary algorithms for global markets across equities, fixed income, currencies, and commodities.
- **BRAIN Platform**: A web-based platform that invites external talent to build and submit predictive signals using WorldQuant’s technology; contributors can earn compensation based on signal quality.
- **Data Exchange**: Enables individuals and organizations to submit data products for evaluation and feedback by WorldQuant’s research team.
- **WorldQuant University**: Provides free, accredited online education – a Master of Science in Financial Engineering and an Applied Data Science Lab.
- **WorldQuant Ventures**: Invests in early-stage technology companies solving real-world problems with emerging technologies.

## Market Standing
- **Valuation/Assets Under Management**: Not publicly disclosed.
- **Key Metric**: >1,100 employees across 28 offices worldwide.
- **Notable Investors/Partners**: Founder Igor Tulchinsky self-funded; partnerships with organizations like AnitaB/Grace Hopper, Correlation One, She Codes, and Women 2.0 for diversity recruiting.
- **Growth Signals**: Global office expansion (28 locations); continuous hiring across research, technology, and portfolio management; launch of AI initiatives led by Co-CIO Paul Griffin; free education programs that build talent pipeline.

## Competitive Advantages
- **Proprietary technology and data infrastructure**: Decisions driven by millions of algorithms and a proprietary platform that processes vast amounts of data.
- **Multi-discipline collaboration**: Researchers, technologists, and portfolio managers work together in “multi-teaming” structures, fostering cross-functional innovation.
- **Global talent model**: Offices in over 15 countries to access diverse talent pools; emphasis on hiring where talent exists rather than centralizing.
- **Culture of transparency and experimentation**: Firm-wide sharing of ideas, regular internal conferences, and innovation sprint projects.
- **Free, accredited education programs** (WorldQuant University) that create a direct recruitment funnel and brand loyalty.

## Strategic Focus
- **Artificial Intelligence**: Co-CIO Paul Griffin leads AI initiatives, with dedicated AI scientist and deep researcher roles being actively hired.
- **Global talent expansion**: Continued hiring across all regions, especially in Asia (Vietnam, India, China) and Eastern Europe (Hungary, Armenia, Romania).
- **Platform diversification**: Growing BRAIN and Data Exchange to crowdsource signals and external data sources.
- **Innovation and diversification**: Researchers participate in dozens of simultaneous innovation projects to explore new asset classes and strategies.

## Why Work Here
- **Culture highlights**: Emphasis on “ideas matter” – knowledge shared through regular firm-wide meetings, external speakers, lecture series, and self-directed learning. Employee-run groups (Multicultural, Pride, Women of WorldQuant, Working Parents). A formal Diversity & Inclusion council meets with senior management.
- **Remote/hybrid/office policy**: Primarily office-based across 28 global locations, but with flexible working arrangements (“freedom and tools they need to deliver results and work in a way that is best for them”).
- **Notable perks**: Leadership mentoring program (WorldQuant Leadership Institute), soft-skills training, multi-teaming for career breadth, and partnerships with external mentorship organizations. Free access to WorldQuant University courses.
- **Engineering culture**: Technologists work alongside researchers and portfolio managers; dedicated Technology Division with roles like AI software developer, data engineer, and C++ developer. Emphasis on inventing new methods and advancing quantitative research.

## Sources
1. [worldquant.com – Company Overview](https://www.worldquant.com/)
2. [worldquant.com – Careers](https://www.worldquant.com/careers/)
3. [worldquant.com – How We Work](https://www.worldquant.com/how-we-work/)
4. [worldquant.com – Who We Are](https://www.worldquant.com/who-we-are/)
5. [greenhouse.io – Jobs at WorldQuant](https://job-boards.greenhouse.io/worldquant/jobs/4565597006)

## Other roles at WorldQuant

- [Junior Execution Trader](https://feeny.ai/job/junior-execution-trader-worldquant-singapore-907vv56w84nc) — Singapore
- [Site Reliability Engineer](https://feeny.ai/job/site-reliability-engineer-worldquant-montevideo-1h3cyn1cqy0k) — Montevideo, Uruguay
- [WQBRAIN User Success Specialist](https://feeny.ai/job/wqbrain-user-success-specialist-worldquant-ho-chi-minh-city-j0hm8asfaxq0) — Ho Chi Minh City, Vietnam
- [Junior Execution Trader](https://feeny.ai/job/junior-execution-trader-worldquant-new-york-pm54atyrjtgg) — New York, NY
- [Quantitative Developer](https://feeny.ai/job/quantitative-developer-worldquant-hanoi-nf4hvemjdsd3) — Hanoi, Vietnam / Ho Chi Minh City, Vietnam
- [Quantitative Developer](https://feeny.ai/job/quantitative-developer-worldquant-old-greenwich-or-be9gbbn3cdep) — Old Greenwich OR, NY
- [Full Stack Developer](https://feeny.ai/job/full-stack-developer-worldquant-new-york-87zn1whne2gh) — New York, NY
- [Senior Engineer](https://feeny.ai/job/senior-engineer-worldquant-delhi-m3ygra9wcc99) — Delhi, India
- [C++ Software Engineer - Data Platform](https://feeny.ai/job/c-software-engineer-data-platform-worldquant-singapore-tbrgrw7p4xxq) — Singapore
- [Executive Assistant and Office Manager](https://feeny.ai/job/executive-assistant-and-office-manager-worldquant-bengaluru-tvbe62k3ng2e) — Bengaluru, India