Hudson River Trading is looking for an ambitious and results-oriented Quant Research Campus Recruiter to join our Campus Recruiting team.
In this role, you will collaborate closely with Campus Recruiters who focus on Talent Attraction (sourcing, marketing, events), while you focus on Talent Evaluation (interviews and offers) and together, we’ll bring exceptional talent to HRT to support the firm’s success and ambitious growth. If you enjoy the challenge of designing effective interview processes, love process and efficiency, and value top-tier candidate experience, we want to meet you!
Responsibilities
- Candidate Management - Take candidates through the interview process for Quant Research intern and full-time positions with a focus on candidate experience
- Pipeline Management - Partner closely with Recruiting Coordinators to ensure a highly efficient and streamlined interview process
- Interview Process - Ideate on how to identify top talent. Collaborate with stakeholders on updates to our evaluation processes
- Offer Process - Manage all aspects of the offer process, from offer approval to offer conversations, negotiation, and closing
- Internship Program - Build strong relationships with interns, partnering with mentors and hiring managers on intern evaluation, in addition to support some programmatic elements
- Stakeholder Management - Collaborate with hiring managers on defining key candidate profiles, developing and iterating on interview processes, and maintaining a high hiring bar
- Make it Better - Make it better is one of our core values. You will be responsible for process improvements in the areas you oversee, which are primarily interview process, offer process, and candidate experience
- Pipeline Metrics - Utilize in-house tools (Greenhouse, Gem, or others) to monitor and improve pipeline metrics. Leverage the data to identify drop-off points or inefficiencies and develop strategies to mitigate them
Qualifications
- 3+ years of experience in full-cycle recruiting with strong exposure to quantitative research hiring and/or experience working with top math and quantitative talent; ideally within the quant finance industry
- Deep understanding of recruiting pipelines for highly selective, technical, or academic talent
- Strong proficiency with ATS and CRM platforms, plus experience working with analytics/reporting tools
- Exceptional organizational, communication, and stakeholder management skills
- Analytical thinker with a process-oriented mindset and a keen attention to detail
- Ability to thrive in a fast-moving environment
The estimated base salary range for this position is $140,000 - $180,000 per year, based on job-related skills and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.
Culture
Hudson River Trading (HRT) brings a scientific approach to trading financial products. We have built one of the world's most sophisticated computing environments for research and development. Our researchers are at the forefront of innovation in the world of algorithmic trading.
At HRT we welcome a variety of expertise: mathematics and computer science, physics and engineering, media and tech. We’re a community of self-starters who are motivated by the excitement of being at the cutting edge of automation in every part of our organization—from trading, to business operations, to recruiting and beyond. We value openness and transparency, and celebrate great ideas from HRT veterans and new hires alike. At HRT we’re friends and colleagues – whether we are sharing a meal, playing the latest board game, or writing elegant code. We embrace a culture of togetherness that extends far beyond the walls of our office.
Feel like you belong at HRT? Our goal is to find the best people and bring them together to do great work in a place where everyone is valued. HRT is proud of our diverse staff; we have offices all over the globe and benefit from our varied and unique perspectives. HRT is an equal opportunity employer; so whoever you are we’d love to get to know you.
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