| Job Position and Company | Posted | Location | Salary | Tags |
|---|---|---|---|---|
Dvtradingπ Remote | $78k - $150k | |||
Dvtradingπ Remote | $105k - $180k | |||
Kronosresearchπ Remote | $105k - $112k | |||
Dvtradingπ Remote | $223k - $225k | |||
ISO 9001 Certified | 400+ students | Learn more | by Metana | ||
Dvtradingπ Remote | $112k - $144k | |||
| $150k - $200k | ||||
| $200k - $300k | ||||
| $125k - $150k | ||||
Gsrmarketsπ Remote | $64k - $86k | |||
| $72k - $99k | ||||
| $98k - $120k | ||||
| $84k - $100k | ||||
| $100k - $150k | ||||
Douro Labsπ Europe | $64k - $90k | |||
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About Us: Founded 20 years ago and headquartered in Chicago, theΒ DV Group of financial services firms has grown to more than 600 people operating throughout North America, Europe and Asia. Since spinning out of a large brokerage firm in 2016, DV Trading has rapidly scaled as an independent proprietary trading firm utilizing its own capital, trading strategies, and risk management methodologies to provide liquidity to worldwide financial markets and hedging opportunities to commodity producers and users. Now, DV group affiliates include two broker dealers, a cryptocurrency market making firm, and a bourgeoning investment adviser. Overview:Β We're looking for a Quantitative Researcher, focused on orderbook-driven signal generation. This role is ideal for someone early in their career who has hands-on experience working with limit orderbook data and a genuine curiosity about how markets function at the tick level. You'll work closely with senior researchers and traders to develop, test, and refine predictive signals and models that inform trading decisions. Β Responsibilities:
Analyze high-frequency limit orderbook data to identify patterns, inefficiencies, and predictive signals Build and backtest quantitative models using historical tick and orderbook data Collaborate with senior researchers and traders to translate research findings into production-ready strategies Develop and maintain data pipelines for processing large-scale, high-frequency market data Apply statistical and machine learning techniques, particularly tree-based methods, to improve signal quality Continuously monitor and iterate on live signals and models based on performance
Requirements:
1β3 years of professional or research experience working directly with orderbook / limit order book (LOB) data Technical degree/background in a quantitative field (Math, Statistics, CS, Physics, Engineering, Financial Engineering) Strong proficiency in Python, including standard data science libraries (pandas, NumPy, etc.) Genuine interest in financial markets and market microstructure β you follow markets, not just models Solid foundation in statistics and quantitative analysis Strong problem-solving skills and intellectual curiosity Ability to communicate technical findings clearly to non-technical stakeholders
Β DV is not accepting unsolicited resumes from search firms. Only search firms with valid, written agreements with DV should submit resumes in response to DVβs posted positions. All resumes submitted by search firms to DV via e-mail, the Internet, personal delivery, facsimile, or any other method without a valid written agreement shall be deemed the sole property of DV, and no fee will be paid in the event the candidate is hired by DV. DV is proud to be an equal opportunity employer and committed to creating an inclusive environment for all employees.
What is a quantitative career?
A quantitative career is a profession that involves using mathematical, statistical, and computational techniques to solve problems and make decisions in a wide range of industries, including finance, engineering, healthcare, and technology
A quantitative career in Web3 involves using mathematical, statistical, and computational techniques to analyze and optimize decentralized finance (DeFi) protocols, blockchain networks, and other Web3 applications
Some examples of quantitative careers include:
- Quantitative Analyst: A professional who uses mathematical models and statistical analysis to identify and quantify risks and opportunities in financial markets.
- Data Scientist: A professional who analyzes complex data using statistical methods, machine learning, and other techniques to help organizations make data-driven decisions.
- Actuary: A professional who uses mathematical models and statistical analysis to assess risk and uncertainty in the insurance and finance industries.
- Quantitative Developer: A professional who develops and implements quantitative models and trading strategies for financial institutions and other organizations.
- Operations Research Analyst: A professional who uses mathematical and statistical techniques to optimize complex systems, such as supply chains, transportation networks, and manufacturing processes.