Applied ML Scientist

Posted 19 Days Ago
Be an Early Applicant
New York, NY
160K-225K Annually
1-3 Years Experience
Financial Services
The Role
The Applied ML Scientist will devise, implement, evaluate, and iterate statistical methods to enhance trading strategies. They will collaborate with senior researchers, investigate novel research ideas, and contribute to research models and technology stack.
Summary Generated by Built In

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.

At PDT, we recognize that certain research directions require both engineering and analytical know-how to execute.  As such, we are looking for a motivated individual that have experience in both software engineering as well as experience in machine learning, statistical modeling, mathematics, or a related field.

Expectations:

  • Collaborate with senior researchers and technologists to investigate novel research ideas, evaluate them with large-scale experiments on a HPC grid.
  • Over time independently originate, test, develop, and own research projects and methodology.
  • Contribute to both our research models and technology stack.

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.

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.

  • Ability to generate and execute on research ideas
  • Exceptional programming skills
  • Knowledge of trading and finance isn’t required
  • Masters (or equivalent experience) in machine learning, computer science, statistics, or a related field

Preferred Qualifications:

  • PhD (or equivalent experience)
  • 5+ years of applied machine learning research experience
  • Strong publication record
  • Experience with the Python scientific stack

The salary range for this role is between $160,000 and $225,000. 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.

Top Skills

Python
The Company
HQ: New York, NY
196 Employees
On-site Workplace

What We Do

PDT, which stands for Process Driven Trading, was founded by Peter Muller in 1993 as a proprietary trading group within Morgan Stanley. In 2013, after establishing a 19-year track record finding inefficiencies in financial markets, the group spun out of Morgan Stanley to become an independent investment management firm, PDT Partners.

Today we are a leader in the field of quantitative finance, known for our rigorous scientific, systematic, and model-driven approach to investing, with multiple billions in assets under management.

Peter Muller, Founder and CEO, and a small group of managing partners lead around 200 scientists, engineers, and professionals in New York and London.

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