Alt Data Equity Quantitative Researcher

Selby Jennings; New York (NY); On-site; USD 180,000 - 350,000; Full time

Job summary

Selby Jennings in NYC is seeking an Equity Quantitative Researcher skilled in leveraging alternative datasets to build systematic strategies. The role focuses on mid-frequency horizons (days/weeks) with plans to expand into global equity markets next year, and emphasizes collaboration and autonomy to develop end-to-end approaches that drive performance.

Ideal candidates bring advanced statistical and mathematical modeling, and are comfortable with ML-enhanced signal research.

Qualifications

• Expert statistical and mathematical modeling skills.
• Experience applying machine learning to signal research is a plus.
• Familiarity with EU/APAC signals is beneficial but not required.

Responsibilities

• Develop end-to-end equity quant strategies using alternative datasets.
• Collaborate in a team with autonomy to push into global equity markets next year.
• Apply linear and non-linear methods to generate signals for mid-frequency horizons.

Skills

Statistical modeling

Mathematical modeling

Machine learning for signal research

EU/APAC signals

Job description

A very profitable Quant Equities team embedded in a Tier-One Quant Fund in NYC is looking for an Equity Quantitative Research skilled in utilizing alternative datasets for systematic strategy development. The existing group focuses on mid-frequency horizons (days/weeks) with plans to push into global equity markets next year. The incoming QR will work in a collaborative setting and be have the autonomy to work on end-to-end strategies to further drive performance in the team.

The team lead has spent a decade with the fund resulting in ample resources to support the team needs. The ideal candidate will be successful in leveraging linear and non-linear methodologies and familiar in working with esoteric datasets that provide significant edge when live. The ideal candidate for this role will have:

• Experience working on EU/APAC signals is a nice to have but not a must
• Expert statistical and mathematical modeling skills (utilizing ML for signal research is a plus)
• Exposure to portfolio construction and execution methodologies