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Interdisciplinary (Computational Social Scientist)

National Science Foundation
Office of Integrative Activities
This job announcement has closed

Summary

The National Science Foundation is seeking qualified candidates for an Interdisciplinary (Computational Social Scientist) position for the Evaluation and Assessment Capabilities Section (EAC). within the Office of the Director (OD), Office of Integrative Activities (OIA) in Alexandria, VA.

For more information on OIA, please click here.

This vacancy will close once 75 applications are recieved.

Overview

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Reviewing applications
Open & closing dates
10/07/2024 to 10/09/2024
This job will close when we have received 75 applications which may be sooner than the closing date. Learn more
Salary
$169,430 to - $204,000 per year
Pay scale & grade
AD 4
Location
FEW vacancies in the following location:
Anywhere in the U.S. (remote job)
Remote job
Yes
Telework eligible
Not applicable, this is a remote position.
Travel Required
Occasional travel - You may be expected to travel for this position.
Relocation expenses reimbursed
Yes—Relocation MAY be paid contingent upon the availability of funds.
Appointment type
Permanent
Work schedule
Full-time
Service
Excepted
Promotion potential
None
Supervisory status
No
Security clearance
Other
Drug test
No
Position sensitivity and risk
Moderate Risk (MR)
Trust determination process
Financial disclosure
Yes
Bargaining unit status
Yes
Announcement number
OIA-24-12563334
Control number
813059100

This job is open to

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Clarification from the agency

Applications will be accepted from all US citizens who meet citizenship and eligibility requirements. Please see the "Other Information" section for further information.

Duties

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This position is in the Office of the Director, Office of Integrative Activities (OIA), Evaluation and Assessment Capabilities Section (EAC). OIA works across disciplinary boundaries to lead and coordinate strategic programs and opportunities that advance interdisciplinary research and innovation across the U.S.; develop critical infrastructure for the nation's STEM enterprise; develop a diverse and engaged next generation of scientists and engineers and expand NSF's impact by producing evidence and information to support decision-making. OIA provides policy and programmatic analytical support to the NSF Director and Deputy Director and, working in partnership with NSF directorates and offices, plays a leadership role in shaping agency-wide policies and new strategic directions that promote cross-Foundation programmatic and operational unity and alignment.

EAC advances the science of science by providing centralized support and resources for data collection, analysis, and design of evaluations, surveys, and enterprise analytics. EAC engages stakeholders to identify learning priorities that drive a broad portfolio of projects that use qualitative and quantitative methods, from simple descriptive analysis to advanced modeling, network analysis, and machine learning. These activities enable NSF to understand program outcomes, evaluate the impacts of investments, make data-informed decisions, and promote a culture of evidence-based planning and policymaking.

The incumbent assists the EAC Section Head, Chief Evaluation Officer, and OIA leadership in formulating scientific goals and program planning through expert knowledge and applying computational methods for program evaluation and science and public policy research and analytics. The incumbent prepares relevant analyses that inform program planning, management, budgetary, and operational decisions in EAC and OIA. The incumbent maintains awareness of current and proposed activities and initiatives that affect EAC, OIA, and/or NSF evidence-building activities and provides advice on the implications of such activities and initiatives on EAC and OIA priority goals and activities. The incumbent will develop and maintain relationships with staff across NSF and other Federal government groups related to data science.

MAJOR DUTIES AND RESPONSIBILITIES

The Computational Social Scientist is responsible for conducting data-driven program evaluations, portfolio analyses, and other studies of NSF research and education programs. The incumbent will use advanced computational and statistical methods to assess various federal initiatives' effectiveness, impact, and outcomes to advance STEM research and education. This position requires a strong background in social science research methodologies and computational data analysis techniques.

  • Design and implement rigorous evaluation methodologies to assess the effectiveness and outcomes of federal STEM and STEM education programs.
  • Collect, clean, and analyze large-scale datasets from diverse sources, including NSF administrative data, surveys, programmatic data, and external data on the science and technology enterprise.
  • Apply advanced statistical and computational techniques to identify trends, patterns, and correlations within complex datasets.
  • Develop and maintain predictive models to forecast program outcomes and inform strategic decision-making.
  • Develop an EAC data and analytics vision and strategic plan. Develop data management policies and practices to ensure data is available, reliable, consistent, accessible, secure, and timely across the office to its mission and activities.
  • Collaborate with interdisciplinary teams of researchers, policymakers, and program managers to interpret findings and communicate results effectively.
  • Prepare comprehensive reports, presentations, and technical documentation summarizing evaluation findings and recommendations for program improvement.
  • Stay abreast of emerging research methodologies, technologies, and best practices in computational social science and program evaluation.
  • Contribute to developing evaluation frameworks, data collection instruments, and evaluation plans for new and existing programs.
  • Provide technical assistance and training to internal and external stakeholders on evaluation methodologies and data analysis techniques.
PROFESSIONAL DEVELOPMENT
  • Establish contacts and maintain active involvement in the Program and related areas through participation in professional activities. Maintain familiarity with salient current research developments. Pursue individual research as workload and travel funds permit.
  • Expand administrative capabilities through training courses or the assumption of new management responsibilities.

Requirements

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Conditions of employment

This position is outside the competitive civil service.

You must meet eligibility and qualification requirements by the closing date of the announcement.

All online applicants must provide a valid email address. If your email address is inaccurate or your mailbox is full/blocked, you may not receive important communication that could affect your consideration for this position.

This position is in the bargaining unit represented by AFGE Local 3403.

The Selected Candidate(s) may be subject to a background investigation.

Qualifications

Candidates must have a Ph.D. in an appropriate field plus after award of the Ph.D., six or more years of successful research, research administration, and/or managerial experience pertinent to the position; OR a Master's degree in an appropriate field plus after award of the degree, eight or more years of successful research, research administration, and/or managerial experience pertinent to the position.

Appropriate Field of Study: Computational social science, social science, statistics, mathematics, computer science, data science, or a related field.

Highly sought-after experience using computational methods to support program evaluation, science or public policy research, or big data analytics.

Education

Please refer to the Qualifications section.

If your degree was obtained from a foreign institution, please also submit the certification from the Association for International Credential Evaluation Professionals, or certification equivalency.

Additional information

Relocation expenses MAY be paid contingent upon the availability of funds.

It is NSF policy that NSF personnel employed at or IPAs detailed to NSF are not permitted to participate in foreign government talent recruitment programs. Failure to comply with this NSF policy could result in disciplinary action up to & including removal from Federal Service or termination of an IPA assignment & referral to the Office of Inspector General. Foreign Talent Definitions

This announcement is open to All US Citizens who meet citizenship and eligibility requirements.

Federal Appropriations Law requires that Non-Citizens meet certain eligibility criteria to be considered. Therefore, Non-Citizens must certify eligibility by signing and attaching this Citizenship Affidavit to their application. Non-citizens who do not provide the affidavit at the time of application will not be considered.

This announcement may be used to fill like positions in other organizations within the National Science Foundation.

NSF has determined that all of its positions are eligible for telework. Work suitable for telework depends on job duties; therefore, employees must receive approval from their supervisor for telework and have a telework agreement in place. Entering into a telework agreement is voluntary.

How you will be evaluated

You will be evaluated for this job based on how well you meet the qualifications above.

You will be evaluated on the extent and quality of your experience, expertise, education, and research activities relevant to the duties of the position. In some cases, additional assessment processes may also be used. We strongly encourage you to specifically address the Quality Ranking Factors below. This will ensure that you receive full consideration in the evaluation process.

Quality Ranking Factors

  1. Expert-level knowledge of data science and data analytics methods and tools, including programming languages such as Python, R, and/or SQL and tools such as Tableau and Microsoft Power BI.
  2. Experience working with large-scale datasets and applying data science and data analytics methods and tools, including machine learning algorithms for predictive modeling and pattern recognition.
  3. Knowledge of quantitative evaluation methods, including experimental design, causal inference, and statistical analysis, particularly in the context of federal STEM research and education programs and science policy evaluation.
  4. Strong communication skills, with the ability to convey technical concepts and findings to non-technical audiences effectively.
  5. Ability to work both independently and collaboratively in a fast-paced, interdisciplinary environment.
  6. Prior experience conducting program evaluations or research in the fields of STEM research, STEM education, STEM workforce development, or related areas is preferred.

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