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Data Scientist Research Associate Jobs (NOW HIRING)

Cedars Sinai

Research Data Scientist

West Hollywood, CA · On-site

$94K - $161K/yr

Bachelor's degree or foreign equivalent in Computer Science, Machine Learning, Applied Mathematics, or related field, plus two (2) years of experience as a Research Data Scientist, Associate ...

Cedars Sinai

Research Data Scientist

West Hollywood, CA · On-site

$94K - $161K/yr

Bachelor's degree or foreign equivalent in Computer Science, Machine Learning, Applied Mathematics, or related field, plus two (2) years of experience as a Research Data Scientist, Associate ...

Visterra

Scientist, Research

Waltham, MA · On-site

Reporting to the Associate Director of Research, the ideal candidate will bring intellectual ... Independently analyze and interpret experimental data, troubleshoot methodological challenges, and ...

Vistera Inc

Scientist, Research

Waltham, MA

Reporting to the Associate Director of Research, the ideal candidate will bring intellectual ... Independently analyze and interpret experimental data, troubleshoot methodological challenges, and ...

Vistera Inc

Scientist, Research

Waltham, MA · On-site

$142K - $167K/yr

Reporting to the Associate Director of Research, the ideal candidate will bring intellectual ... Independently analyze and interpret experimental data, troubleshoot methodological challenges, and ...

Contemporaries

Be Seen First

Data Scientist

Durham, NC · Remote

$51 - $58/hr

Collaborate with researchers, analysts, and leadership teams supporting environmental and public health initiatives Minimum Qualifications * Bachelor's degree in Data Science, Computer Science ...

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How much do data scientist research associate jobs pay per year?

As of Jun 6, 2026, the average yearly pay for data scientist research associate in the United States is $68,039.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,000.00 and $59,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Scientist Research Associate, and why are they important?

To thrive as a Data Scientist Research Associate, you need a solid background in statistics, machine learning, and data analysis, generally supported by a degree in computer science, statistics, or a related field. Familiarity with programming languages such as Python or R, experience with data visualization tools, and knowledge of platforms like SQL and TensorFlow are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help you excel in collaborative research environments. These skills and qualities are crucial for generating actionable insights from data and advancing research objectives.

What is a Data Scientist Research Associate?

A Data Scientist Research Associate is a professional who applies statistical analysis, machine learning, and data management techniques to conduct research and extract insights from complex datasets. They often work in academic, government, or industry research settings, supporting projects by designing experiments, analyzing large volumes of data, and interpreting results. Their work helps inform decision-making, advance scientific knowledge, and develop new data-driven solutions. Typically, they collaborate with multidisciplinary teams and may contribute to publishing research findings.

What are some typical challenges faced by Data Scientist Research Associates when working on interdisciplinary projects?

Data Scientist Research Associates often collaborate with experts from fields such as engineering, biology, or social sciences. A common challenge is bridging the communication gap between disciplines, as each may have its own jargon and methodologies. Additionally, integrating and preprocessing diverse datasets can be complex due to varying data formats and quality. Overcoming these challenges requires strong communication skills, adaptability, and a willingness to learn about domain-specific concepts to ensure productive teamwork and successful project outcomes.
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Postdoctoral Research Associate - Data Scientist

Postdoctoral Research Associate - Data Scientist

Oak Ridge National Laboratory

Oak Ridge, TN • On-site

Full-time

Posted 16 days ago

Oak Ridge National Laboratory rating

9.3

Company rating: 9.3 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

4th of 103 rated laboratories

Job description

Requisition Id 16485
Overview:
The Data and AI Systems Research Section within the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is seeking a postdoctoral researcher to join the Workflow Systems Group and help advance the use of AI in scientific discovery. This position centers on scientific machine learning, automated AI/ML optimization, and high-performance computing (HPC), with an emphasis on developing intelligent systems that can accelerate large-scale scientific research on leadership-class supercomputers.
The successful candidate will contribute to research efforts supported by the U.S. Department of Energy Office of Science, including the Advanced Scientific Computing Research (ASCR) program and the Genesis initiative. These programs focus on integrating AI directly into scientific workflows to enable autonomous, data-driven discovery in areas such as fusion energy, materials science, climate science, and nuclear energy.
As part of ORNL's interdisciplinary research environment, you will work alongside scientists, engineers, and computational researchers while leveraging world-class computing resources, including Frontier, the world's first exascale supercomputer. The role includes developing and advancing open-source software for large-scale hyperparameter optimization (HPO), neural architecture search (NAS), and Bayesian optimization on distributed HPC systems.
Research activities will address key challenges in AI for science, including surrogate modeling, uncertainty quantification, and multi-fidelity optimization for complex simulation workflows. This position offers an opportunity to contribute to cutting-edge AI and HPC research while supporting DOE's broader mission to advance scientific innovation through computational science.
The appointment length is 2 years with the possibility of extension, subject to performance and availability of funding.
Major Duties and Responsibilities:
  • Conduct research and development in scalable AI/ML methods for scientific computing and high-performance computing environments.
  • Develop and evaluate optimization techniques for machine learning workflows, including approaches for model tuning, automated model design, and adaptive search strategies.
  • Contribute to research in uncertainty quantification, surrogate modeling, and other methods that improve the robustness and reliability of AI-driven scientific applications.
  • Design and implement distributed and parallel approaches that efficiently leverage large-scale computing resources, including heterogeneous CPU/GPU systems, along with the possibility of working with Quantum computing.
  • Collaborate with interdisciplinary research teams to integrate AI/ML capabilities into scientific simulation, data analysis, and computational workflows.
  • Contribute to the development and maintenance of open-source software, including testing, documentation, and user support activities.
  • Work closely with researchers and domain scientists to communicate results, define research directions, and support collaborative projects.
  • Publish research findings in peer-reviewed journals and present work at scientific workshops and conferences.
  • Design and implement scalable AI/ML optimization algorithms for hyperparameter optimization and neural architecture search, targeting scientific machine learning models running on leadership-class HPC systems.
  • Deliver ORNL's mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace - in how we treat one another, work together, and measure success.

Basic Qualifications:
  • A PhD in Computer Science, Applied Mathematics, Computational Science, Data Science, or a related discipline completed within the last three years.
  • An excellent record of productive and creative research as demonstrated by publications in top peer-reviewed journals and conferences.
  • Demonstrated experience with machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn) and hyperparameter optimization or AutoML techniques.
  • Proficiency in Python and familiarity with software engineering best practices (version control, testing, documentation).
  • Experience with HPC environments and parallel/distributed computing.
  • Strong problem-solving and communication skills, with the ability to work collaboratively in a team setting.

Preferred Qualifications:
  • Experience with multi-fidelity optimization, neural architecture search, or large-scale AutoML systems.
  • Familiarity with surrogate modeling, physics-informed neural networks, or uncertainty quantification for scientific applications.
  • Prior exposure to DOE workflows, national laboratory environments, or large-scale simulation codes.
  • Experience contributing to open-source scientific software projects.

#LI-DC1
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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