Job summary
Job post source
This job is from a recruiting firm hiring for a separate company.
Job overview
The Senior Quantitative Researcher role involves building and expanding a systematic equity trading program, contributing to the firm's investment strategies and performance.
Responsibilities and impact
The candidate will design, test, and deploy equity and futures trading factors, develop and maintain research tools and risk models, collaborate with quant developers to implement strategies in production, and work closely with the PM and CTO to shape the research roadmap.
Compensation and benefits
The position offers a top-decile base salary with an uncapped bonus directly linked to performance, potential sign-on bonuses, and relocation support for NYC or CT locations with hybrid work options for exceptional candidates.
Experience and skills
Candidates should have a PhD or MS with equivalent publications, 5-10 years of systematic research experience at hedge funds or similar, proficiency in Python and kdb+/q, and a strong track record in signal generation, portfolio optimization, and risk control.
Career development
Opportunities include being among the first hires in a new equity pod, setting standards for code and ideas, and direct impact on the firm's trading strategies with a flat structure enabling rapid deployment and ownership.
Work environment and culture
The company operates like a startup with low bureaucracy, a flat structure, rapid deployment, and direct P&L linkage, emphasizing intellectual humility and data-driven decision-making.
Company information
The client is a profitable, tech-driven systematic fund managing $2-3 billion in assets, focused on mid-frequency equity strategies with a startup-like culture.
Team overview
The candidate will join the first 10 hires in the equity pod, working closely with the PM and CTO in a collaborative environment.
Job location and travel
The job is based in NYC or Connecticut with relocation support and hybrid work options for exceptional talent.
Application process
Applicants are encouraged to apply or contact the recruiter for a confidential chat; US work authorization is required, and visa transfer is considered for top candidates.
Unique job features
This role offers a greenfield build opportunity with full ownership from idea to production, direct P&L linkage, and the chance to see live trading impact of research signals.
Company overview
DeepRec.ai is a technology company based in Los Angeles, California, specializing in advanced artificial intelligence and machine learning solutions. The company focuses on computer vision, data science, and predictive modeling to develop cutting-edge technologies. DeepRec.ai makes money by offering high-impact AI solutions and hiring top-tier talent for roles such as data scientists, computer vision engineers, and machine learning scientists. The company also fosters a community of innovators and deep tech enthusiasts through initiatives like the DeepRec.AI Leadership Lab, which aims to decode the future of technology.
How to land this job
Tailor your resume to highlight your expertise in systematic equity research, emphasizing your experience with alpha discovery, signal generation, and portfolio optimization to align with DeepRec.ai's focus on mid-frequency equity programs.
Showcase your proficiency in Python, especially with pandas and NumPy, and mention any experience with kdb+/q or other high-performance data stores, as these are critical technical skills for the role.
Apply through multiple channels including DeepRec.ai's corporate career site, LinkedIn, and any hedge fund or quantitative finance job boards to maximize your application visibility.
Connect with current employees in DeepRec.ai’s quantitative research or systematic equity teams on LinkedIn; use ice breakers like commenting on recent research initiatives or expressing enthusiasm for their greenfield equity pod build to start meaningful conversations.
Optimize your resume for ATS by incorporating keywords from the job description such as 'alpha discovery,' 'systematic research,' 'Python,' 'kdb+/q,' 'portfolio optimization,' and 'risk control' to ensure it passes initial screenings.
Utilize Jennie Johnson's Power Apply feature to automate tailored applications, identify all relevant job posting sites, and find LinkedIn connections, saving you time and increasing your chances of landing the Senior Quantitative Researcher role at DeepRec.ai.
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