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Applied ML Scientist
PDT Partners · New York, NY · Hybrid · Active · $190,000–$250,000 / year · Greenhouse
Job facts
| Field | Value |
|---|---|
| Company | PDT Partners |
| Title | Applied ML Scientist |
| Normalized title | - |
| Department / team | Research / Strategies |
| Location | New York, NY, United States |
| Work model | Hybrid / Hybrid |
| Employment type | Full Time |
| Salary | $190,000–$250,000 / year |
| Status | active |
| ATS provider | Greenhouse |
| Posted / first seen | — / 2026-05-29 |
| Changed / last seen | 2026-05-29 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from PDT Partners. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Greenhouse. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in New York. | Open |
| Department jobs | Active postings in Research / Strategies. | Open |
| Work model jobs | Active Hybrid postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | PDT Partners |
| Source | 5649c28f-4667-4aa0-8f8b-1c1763f626ef |
| ATS provider | Greenhouse |
Description
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.
PDTers are creative, energetic, friendly, entrepreneurial, and collaborative. If you could walk around our office, you’d see that we’re a focused, intent, and nimble company with none of the attitude and bureaucracy of a stereotypical Wall Street trading firm. We love to work on challenging and complicated problems, that in return give a chance to make outsized, direct impact on our bottom line. For the right talent, there is fantastic growth potential.
This is a hybrid position and will require the person to work from our New York City office at minimum 3 days a week.
Why join us?
PDT Partners has a 30+ year track record and a reputation for excellence. Our goal is to be the best quantitative investment manager in the world—measured by the quality of our products, not their size. PDT’s very high employee-retention rate speaks for itself. Our people are intellectually extraordinary and our community is close-knit, down-to-earth, and diverse.
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
Below is a list of skills and experiences we think are relevant. Even if you don’t think you’re a perfect match, we still encourage you to apply because we are committed to developing our people
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
Finance knowledge is not required or expected
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
The salary range for this role is between $190,000 and $250,000. This range is not inclusive of any potential bonus amounts. Factors that may impact the agreed upon salary within the range for a particular candidate include years of experience, level of education obtained, skill set, and other external factors.
PRIVACY STATEMENT: For information on ways PDT may collect, use, and process your personal information, please see PDT’s privacy notices .
Full job record
| Job ID | e49c2092a945536c8f144d0694aceaf44900d2ca |
| Org ID | 72e4ca55-e0b7-488c-a165-b11a9162c308 |
| Source ID | 5649c28f-4667-4aa0-8f8b-1c1763f626ef |
| Board ID | 5649c28f-4667-4aa0-8f8b-1c1763f626ef |
| Provider | greenhouse |
| Provider Job Key | 1473516 |
| Title | Applied ML Scientist |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | New York, NY |
| Department | Research / Strategies |
| Team | — |
| Employment Type | Full-time |
| Workplace Type | hybrid |
| Remote Policy | hybrid |
| Country | United States |
| Region | NY |
| City | New York |
| Salary Raw | salary range for this role is between $190,000 and $250,000 |
| Salary Min | 190,000 |
| Salary Max | 250,000 |
| Salary Currency | USD |
| Salary Period | year |
| Source URL | https://job-boards.greenhouse.io/pdtpartners/jobs/1473516 |
| Apply URL | https://job-boards.greenhouse.io/pdtpartners/jobs/1473516 |
| First Seen At | 2026-05-29 22:58:13Z |
| Last Seen At | 2026-06-06 20:24:00Z |
| Last Checked At | 2026-06-06 20:24:00Z |
| Last Changed At | 2026-05-29 22:58:13Z |
| Inactive At | — |
| Source Posted At | — |
| Source Updated At | 2026-05-27 17:45:27Z |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=greenhouse/board=pdtpartners/date=2026-06-06/2026-06-06T20-24-00-420Z-be73794cbf787aa38d94e25f3c26139b940784c2ad3a252a7eacd2c6087502ae.json |
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