Data Scientist

Argonne National Laboratory

United States

On-site

USD 94,000 - 147,000

Full time

10 days ago

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Job summary

Argonne National Laboratory seeks a Data Scientist to join the Field Intelligence Element (FIE) to develop and apply machine learning and advanced statistics for processing experimental data. You will collaborate with software engineers to document methods for reuse and support the transition of algorithms from research to prototype-ready deployment.

You will assist in planning project direction, contribute to field testing, and travel up to 15% domestically and internationally. U.S.

Qualifications

  • Graduate degree in physics or physical chemistry with experience using advanced statistical methods for data analysis.
  • Familiarity with machine learning techniques applicable to problems with limited training data.
  • Proficiency in Python and R for data analysis and modeling.

Responsibilities

  • Develop and apply new ML and statistical methods for processing experimental data.
  • Maintain, enhance, and document existing statistical analysis methods used by the group.
  • Collaborate with software engineers to deploy algorithms from research to prototype-ready deployment.
  • Assist in long-term project direction and scope planning.

Skills

Python
R
Machine learning
Statistics
Bayesian methods
Frequentist methods
Data analysis
Communication

Education

Graduate degree in physics or physical chemistry

Job description

We are seeking a talented Data Scientist to join the Field Intelligence Element (FIE). The FIE enables Argonne National Laboratory to provide products and services to DOE’s Office of Intelligence and Counterintelligence (DOE-IN), the Intelligence Community (IC), and non-IC federal agencies.

Primary Responsibilities
  • Develop and apply new machine learning and statistical analysis methods for processing experimental data
  • Maintain, enhance, and document existing statistical analysis methods used by the group
  • Collaborate with software engineers to support the transition of algorithms from research to prototype-ready deployment
  • Assist in long-term planning of project direction and scope as new opportunities arise.
  • Assist software engineers with in-field integration, testing, and operational support of new algorithms
  • Conduct testing and evaluation of new algorithms based on theoretical analysis and experimental evaluation
  • Ability to travel up to 15% of the time, including domestic and international field travel to deploy, test, develop, and collect data on sensor and monitoring systems.
Position Requirements
  • A graduate degree in physics or physical chemistry and experience using advanced statistical methods for data analysis
  • Possess familiarity with machine learning techniques applicable to problems with limited training data
  • Ability to program in a variety of languages, including Python and R
  • Familiarity with nuclear physics and gamma spectroscopy
  • Familiarity with both Bayesian and frequentist statistical concepts and methods
  • Experience applying statistical concepts to detection/classification problems
  • To perform the essential functions of this position successful applicants must provide proof of U.S. citizenship, which is required to comply with federal regulations and contract. The selected candidate will be required to obtain and maintain a clearance. Please see http://www.state.gov/m/ds/clearances/c10978.htm for more information about requirements for obtaining a security clearance process

The selected candidate will be placed at the appropriate level (RD2 or RD3) depending upon the depth and breadth of relevant knowledge, skills, and experience brought to the position. The requirements for the desired levels are as follows:

  • RD2 Level : Bachelors and 5+ years; Master’s and 3+ years; Doctorate and 0+ years in physics or physical chemistry, or equivalent. The expected pay range for this position is $94,486 - $147,399.
  • RD3 Level : Bachelor’s and 8+ years; Master’s and 5+ years; Doctorate and 4+ years in physics or physical chemistry, or equivalent. The expected pay range for this position is $116,250 - $181,350.
Job Family

Research Development (RD)

Job Profile

Software Engineering 2

Worker Type

Regular

Time Type

Full time

The expected hiring range for this position is $94,486.00 - $147,398.94.

Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.

As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.

Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.

All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.

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