Alternative Data Researcher, Equities

Reposted 9 Days Ago
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New York, NY
Mid level
Financial Services
The Role
The Alternative Data Researcher will focus on quantitative analysis of external datasets for systematic equities strategies. This role involves collaborating with data teams, testing dataset additivity, developing analysis techniques, and implementing trading signals.
Summary Generated by Built In

About the Position

We are looking for an Alternative Data Researcher to work on quantitative analysis of external datasets. Your work will focus on systematic equities strategies to start, but will have the potential to expand to different asset classes and to semi-systematic trading. 

You’ll be involved in the whole pipeline, including coordinating with our Data Engineering team to find and onboard new datasets, testing whether a new dataset is additive to our modeling, developing new techniques for analyzing datasets, and defining and implementing signals and trading schedules.

We are looking for someone who has worked with alternative datasets and understands both the landscape of alternative data and problems specific to the area, including (but not limited to) data causality and data crowding. You should be excited to dig into the details along all parts of this process, including thinking about optimal trading schedules, defining new features, examining data for outliers and general data quality issues, as well as shaping the higher-level direction of our alt-data strategy and the growth of our alt-data team.

The problems we work on rarely have clean, definitive answers, and they often require insights from people across the firm with different areas of expertise. We find that we make the most progress when team members collaborate and communicate fluidly. Your success in this role will depend on your ability to balance expertise and intellectual rigor with an open mind to a variety of techniques and modes of thinking.

About You

  • 2-6 years of professional experience performing systematic quantitative analysis of alternative datasets, ideally with experience in equities
  • Have strong quantitative skills and understand the alt-dataset landscape 
  • Able to think about domain-specific questions, as well as general research topics such as data causality, feature engineering, and portfolio construction
  • Team player with a highly collaborative mindset; communicates clearly and often and enjoys discussing research ideas and results in depth

If you're a recruiting agency and want to partner with us, please reach out to [email protected].

Top Skills

Alternative Datasets
Data Engineering
Feature Engineering
Portfolio Construction
Quantitative Analysis
Systematic Trading
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The Company
HQ: New York, NY
1,390 Employees
On-site Workplace
Year Founded: 2000

What We Do

Jane Street works differently. As a liquidity provider and market maker, we trade on more than 200 trading venues across 45 countries and help form the backbone of global markets. Our approach is rooted in technology and rigorous quantitative analysis, but our success is driven by our people.

Our bright, beautiful offices in the heart of New York, London, Hong Kong, and Amsterdam are open and buzzing with conversation. We come from many backgrounds and encourage travel between offices to share perspectives. Some of our best ideas come from bumping into a visiting colleague at the office coffee bar.

Markets move fast. Staying competitive as we’ve grown has required constant invention—of new trading strategies, technology, and processes. We’ve found this is easier when you hire humble, kind people. They tend to help each other, and prioritize teamwork over titles.

We invest heavily in teaching and training. There’s a library and a classroom in every office, because deepening your understanding of something is considered real work. Guest lectures, classes, and conferences round out the intellectual exchanges that happen every day.

People grow into long careers at Jane Street because there are always new and interesting problems to solve, systems to build, and theories to test. More than twenty years after our founding, it still feels like we’re just getting started.

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