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Form of workEngineers Gate (EG) is a leading quantitative investment company focused on computer-driven trading in global financial markets. We are a team of researchers, engineers, and financial industry professionals using sophisticated statistical models to analyze data and identify predictive signals to generate superior investment returns. EG's differentiated model provides Portfolio Managers with extensive resources to efficiently build and scale their portfolios. Our state-of-the-art technology and data platform along with our patient capital allocation approach allows Portfolio Managers and their teams to focus more on innovation and alpha research instead of operations.
We are seeking a talented and highly motivated candidate for the role as a Junior Quantitative Equities Portfolio Manager. In this position, you will play a pivotal role in building and managing a Quantitative Equities market neutral strategy under the guidance of our Senior Portfolio Manager. This is a highly collaborative environment, both within the team and across the firm, making it an ideal opportunity for the candidate looking to transition from a Researcher role into their first Portfolio Manager position. We place a high value on continuous learning and development and this role represents a unique opportunity to work alongside and learn from highly experienced quantitative trading teams.
Joining Engineers Gate offers a unique opportunity to work at the forefront of systematic trading, where innovation and quantitative analysis intersect. We are passionate about implementing scientific and mathematical methods to explore and solve problems in the global financial markets. If you thrive in a fast-paced, data-driven environment, we encourage you to apply.
Key Responsibilities- Work collaboratively with the Senior Portfolio Manager to develop and implement mid-frequency Quantitative Equities market neutral strategies.
- Conduct research and analysis to identify new trading opportunities and refine existing strategies.
- Assist in the optimization of trading models and risk management processes.
- Monitor portfolio performance and make necessary adjustments to achieve desired risk-return objectives.
- Leverage Python programming to develop tools and models that facilitate portfolio management and research processes.
- Take a proactive approach to problem-solving, demonstrating a high level of motivation and initiative in the pursuit of innovative portfolio management strategies.
- Collaborate closely with cross-functional teams of researchers, engineers, and financial industry professionals.
- Stay informed about market trends and developments to stay at the forefront of quantitative finance.
- 5-10 years of relevant experience as either a Researcher or Portfolio Manager focused on Quantitative Equities market neutral strategies.
- Proven track record of designing and implementing successful strategies with a minimum of $100 million in Gross Market Value (GMV) traded with live capital.
- High proficiency in Python for quantitative research and model development.
- Solid understanding of statistical analysis, risk management, and portfolio optimization.
- Familiarity with mid-frequency trading strategies, although open to high- and low-frequency strategies as well.
- Effective communicator with the ability to work collaboratively in a team environment.
- Availability for an immediate or very near-term start is a plus.
Joining Engineers Gate offers a unique opportunity to work at the forefront of systematic trading research, where innovation and quantitative analysis intersect. We are passionate about implementing scientific and mathematical methods to explore and solve problems in the global financial markets. If you thrive in a fast-paced, data-driven environment, we encourage you to apply.
The salary range for this role is anticipated to be between $120K and $150K. This range does not include any potential bonus amounts, other forms of compensation, or benefits offered. Actual compensation for successful candidates will be carefully determined based on a number of factors, including the candidate's skills, qualifications, education and experience.
