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Applied ML Scientist
Job in
New York, New York County, New York, 10261, USA
Listed on 2026-06-12
Listing for:
Gravity Engineering Services Pvt Ltd.
Part Time
position Listed on 2026-06-12
Job specializations:
-
IT/Tech
Data Scientist
Job Description & How to Apply Below
About the Role
PDT, a quantitative investment manager, is hiring problem solvers who blend programming and applied research experience. Individuals in this role will devise, implement, evaluate, and iterate to create and improve statistical methods vetting them through direct application to enhancing our trading strategies. Applied ML scientists are expected to navigate quantitative and technical challenges within a project to advance our research methodology.
They will have ample opportunity to collaborate with our deep bench of senior researchers and technologists.
This is a hybrid position and will require the person to work from our New York City office at minimum 3 days a week.
Responsibilities- Work closely with senior researchers on a variety of trading strategies and research projects, with the opportunity to conduct independent research and originate research topics over time
- Contribute to the long-term success of our research-driven algorithmic trading business
- Solid mathematical and analytical ability
; exceptional problem-solving and modeling ability - Research intuition
- Experience in programming (
Python, R, Matlab, C++) - Excellent communication and collaborative white board skills
- Meticulous and detail-oriented, and innately driven to understand issues deeply
- Experience with/interested in working with large data sets
- Self-motivated and highly-productive, with a strong sense of ownership and urgency
- Able to work collaboratively and productively with others
- Enjoy solving complex, difficult, real-world problems
- Entrepreneurial and creative
- PhD preferred
- Undergraduate or Masters degree with equivalent industry experience in machine learning
- 2+ years of applied machine learning research experience
- Strong publication record
- Experience with the Python scientific stack
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