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Remote Algorithmic Trading Quant Jobs in Tennessee

Data Scientist II

Memphis, TN · On-site +1

$13K/mo

... or a related quantitative field. Minimum Experience: At least two (2) years of professional ... This position is eligible for remote work and may be located anywhere within the United States ...

New

Remote Algorithmic Trading Quant information

What is a Remote Algorithmic Trading Quant?

A Remote Algorithmic Trading Quant is a quantitative analyst who develops, tests, and implements mathematical models and trading algorithms for financial markets while working off-site or from home. They analyze large datasets, identify trading opportunities, and use programming languages like Python or C++ to automate trading strategies. Their work is vital for firms seeking to gain a competitive edge through data-driven, automated trading, and being remote allows them to collaborate with global teams or firms without being physically present in a traditional office setting.

What is the difference between Remote Algorithmic Trading Quant vs Remote Quantitative Analyst?

AspectRemote Algorithmic Trading QuantRemote Quantitative Analyst
CredentialsDegree in finance, computer science, or mathematics; coding skills; experience with trading algorithmsDegree in finance, economics, mathematics; statistical and analytical skills; programming knowledge
Work EnvironmentFinancial firms, hedge funds, trading firms; focus on developing and testing trading algorithmsFinancial institutions, investment firms; focus on data analysis, modeling, and risk assessment
Industry UsageCommon in trading and hedge fund industriesWidespread across finance, banking, and investment sectors

The Remote Algorithmic Trading Quant specializes in developing and implementing trading algorithms within trading firms, focusing on automation and execution strategies. In contrast, the Remote Quantitative Analyst often performs broader data analysis and modeling tasks across various financial sectors. While both roles require strong quantitative skills and programming knowledge, their primary focus and work environments differ, aligning with their specific industry functions.

What are the key skills and qualifications needed to thrive as a Remote Algorithmic Trading Quant, and why are they important?

To thrive as a Remote Algorithmic Trading Quant, you need advanced quantitative skills, strong programming ability (often in Python, C++, or R), and a solid background in mathematics, statistics, or related fields—typically supported by a relevant degree. Familiarity with trading platforms, financial data feeds, and version control systems, as well as experience with backtesting frameworks, is highly valued. Exceptional problem-solving, attention to detail, and effective remote communication are crucial soft skills for success in this position. These skills and qualities enable the development, testing, and deployment of robust trading strategies in a fast-paced, data-driven environment.

What are some common challenges faced by remote algorithmic trading quants, and how can they be addressed?

Remote algorithmic trading quants often face challenges such as ensuring robust communication with team members, maintaining access to secure and reliable data feeds, and collaborating effectively across time zones. To address these, quants typically use advanced collaboration tools, participate in regular virtual meetings, and follow strict cybersecurity protocols. Building strong documentation and leveraging version-control systems like Git can also help maintain workflow efficiency and code integrity while working remotely.
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Nonproliferation Data Scientist

Nonproliferation Data Scientist

Oak Ridge National Laboratory

Oak Ridge, TN • On-site, Remote

Full-time

Posted 26 days ago


Oak Ridge National Laboratory rating

8.8

Company rating: 8.8 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

10th of 105 rated laboratories


Job description

Requisition Id 16639 

Overview:

We are seeking a Nonproliferation Data Scientist to join the Data Science and Engineering for Nonproliferation Group in the National Security Sciences Directorate. In this role, you will develop and apply advanced data science, machine learning, and statistical approaches to challenging problems in nuclear nonproliferation and national security.

The successful candidate will work closely with multidisciplinary teams of data scientists, software engineers, physicists, and domain experts to develop innovative analytic capabilities that support nuclear material detection, characterization, safeguards, and nuclear fuel cycle analysis. This position provides the opportunity to conduct impactful research while contributing to the development of next-generation scientific software and data-driven methods for national security applications.

Major Duties and Responsibilities

  • Conduct research and development applying machine learning, statistical modeling, optimization, and data science methods to nuclear nonproliferation challenges.
  • Develop, evaluate, and apply data-driven algorithms, selecting appropriate analytical approaches based on problem characteristics, available data, and mission objectives.
  • Develop and maintain scientific software and analytic tools that enable advanced data analysis, modeling, and decision support.
  • Collaborate with multidisciplinary teams of domain scientists, software developers, and researchers to integrate advanced analytics into mission applications.
  • Design and execute computational studies to assess algorithm performance, quantify uncertainty, and generate actionable insights from complex datasets.
  • Communicate research findings through technical reports, publications, presentations, and interactions with sponsors and collaborators.
  • Contribute to proposal development, program growth activities, and new research initiatives.
  • Ensure all work is performed safely, securely, and in accordance with ORNL policies and procedures.

All team members deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. We foster a respectful, team-focused environment where all individuals can contribute and succeed.

Basic Qualifications

  • PhD in data science, computer science, statistics, mathematics, physics, engineering, or a related quantitative field; or an MS in one of these disciplines with a minimum of two years of relevant experience.
  • Demonstrated experience applying machine learning, statistical analysis, optimization, or related data science techniques to solve complex technical problems.
  • Experience developing software for scientific computing, data analysis, or machine learning applications.
  • Proficiency in Python and common scientific computing and machine learning libraries.
  • Strong written and verbal communication skills, including experience presenting technical results to scientific or technical audiences.

Preferred Qualifications

  • Experience with machine learning, artificial intelligence, statistical modeling, uncertainty quantification, optimization, or scientific machine learning methods.
  • Demonstrated ability to evaluate alternative analytical approaches and determine when different algorithms or modeling techniques are most appropriate for a given problem.
  • Experience with research software development practices, including version control, testing, reproducibility, and collaborative software engineering.
  • Experience with open-source scientific software projects.
  • Familiarity with high-performance computing, cloud computing, or large-scale data analytics environments.
  • Knowledge of nuclear nonproliferation, safeguards, nuclear fuel cycle analysis, remote sensing, or related national security mission areas.
  • Record of peer-reviewed publications, conference presentations, or other research accomplishments.
  • Experience working in multidisciplinary research environments involving both domain scientists and software developers.
  • Familiarity with modern AI/ML frameworks such as PyTorch, TensorFlow, JAX, or related tools.

Special Requirements: 

  • This position requires the ability to obtain and maintain a Secret Compartmented Information (SCI) clearance from the Department of Energy. As such, this position is a Workplace Substance Abuse (WSAP) testing designated position. WSAP positions require passing a pre-placement drug test and participation in an ongoing random drug testing program.  In addition, due the SCI, you may also be subject to random polygraph testing. 

This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.


If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.


ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply.  UT-Battelle is an E-Verify employer.


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