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Quantitative Researcher - Fast Forecasting & Trading - Equities

Two Sigma

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Job Details

Location: 147 Fremont Ave, Staten Island, NY 10306, USA Posted: Jun 06, 2024

Job Description

Two Sigma is a financial sciences company, combining data analysis, invention, and rigorous inquiry to help solve the toughest challenges in investment management, insurance technology, securities, private equity, and venture capital. Our team of scientists, technologists, and academics looks beyond the traditional to develop creative solutions to some of the world’s most complex financial problems. The Fast Forecasting & Trading team within Two Sigma is looking for a quantitative researcher with experience in intraday signal research and monetization. This role will focus on expanding our mid-frequency (intraday) trading business by improving the execution and monetization of our existing intraday signals, along with generating new alphas from microstructure data patterns and exploring new liquidity sources and trading opportunities. You will take on the following responsibilities:
  • Improve the monetization and execution of our existing signal pool by studying their market impact and refining trade construction. This will involve close collaboration with other researchers and the development of tools to enhance the monetization of our intraday signals.
  • Analyze microstructure data using traditional and ML methods to identify trading patterns and develop features and trading signals. You will be responsible for researching new signal ideas and implementing them on our intraday trading platform.
  • Identify new liquidity sources and enhance our ability to access them through quantitative research and collaboration with engineering partners to build necessary trading capabilities.
  • Focus primarily on equity markets, but contributions to other asset classes are a bonus.
You should possess the following qualifications:
  • Minimum 3 years of experience in trading and monetizing mid-frequency signals and strategies. Familiarity with trading closing and opening auctions is preferred.
  • Knowledge of global equity market microstructure, including North America, Europe, and Asia. Experience with other asset classes is a plus.
  • Hands-on experience analyzing microstructure data and extracting patterns from them, preferably using modern machine learning tools.
  • Proficiency in working with order book and tick data using high-performance languages like Rust or C++.
  • Advanced degree (masters or higher) in a technical or quantitative field, such as statistics, mathematics, physics, electrical engineering, or computer science.
You will enjoy the following benefits:
  • Core Benefits: Fully paid medical and dental insurance premiums for employees and dependents, competitive 401k match, employer-paid life & disability insurance
  • Perks: Onsite gyms with laundry service, wellness activities, casual dress, snacks, game rooms
  • Learning: Tuition reimbursement, conference and training sponsorship
  • Time Off: Generous vacation and unlimited sick days, competitive paid caregiver leaves
  • Hybrid Work Policy: Flexible in-office days with budget for home office setup
The base pay for this role will be between $165,000 and $300,000. This role may also be eligible for other forms of compensation and benefits, such as a discretionary bonus, health, dental and other wellness plans and 401(k) contributions. Discretionary bonus can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their skills, qualifications and experience. We are proud to be an equal opportunity workplace. We do not discriminate based upon race, religion, color, national origin, sex, sexual orientation, gender identity/expression, age, status as a protected veteran, status as an individual with a disability, or any other applicable legally protected characteristics.

About Two Sigma

Two Sigma is a systematic investment manager, founded with the goal of applying cutting-edge technology to the data-rich world of finance

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