1

Internship Data Science Economics Jobs in Washington

Bachelor of Science degree in a relevant field such as statistics, computer science, economics, mathematics, analytics, data science, business, or social sciences * 5-10+ years of experience in data ...

Showing results 21-40

Internship Data Science Economics information

What is an internship in data science economics?

An Internship in Data Science Economics is a temporary position that allows students or recent graduates to gain practical experience applying data science techniques to economic problems. Interns typically work on projects involving data analysis, statistical modeling, and economic research, often using programming languages like Python or R. The role helps bridge the gap between academic knowledge and real-world applications, providing valuable skills for a future career in data science or economics.

What types of projects do interns typically work on in a data science economics internship?

Interns in Data Science Economics roles often work on projects involving data analysis, economic modeling, and statistical research to support business decision-making. These projects may include analyzing large datasets to identify economic trends, building predictive models, and creating visualizations to communicate insights. Interns usually collaborate closely with both data scientists and economists, gaining exposure to real-world applications of economic theories and data-driven problem-solving. This hands-on experience helps interns develop technical and analytical skills while contributing meaningful work to the team.

What are the key skills and qualifications needed to thrive as an internship data science economics, and why are they important?

To thrive as an Internship Data Science Economics, you need a solid background in statistics, econometrics, and programming languages like Python or R, typically supported by progress toward a degree in economics, data science, or a related field. Familiarity with data analysis tools such as SQL, statistical software, and visualization platforms like Tableau is often required. Strong analytical thinking, effective communication, and the ability to collaborate in team environments help interns excel in this role. These skills are crucial for interpreting economic data, delivering actionable insights, and supporting informed decision-making within organizations.

What is the difference between Internship Data Science Economics vs Data Analyst Intern?

AspectInternship Data Science EconomicsData Analyst Intern
Required SkillsStatistics, economics, programming (Python/R), data analysisData analysis, Excel, SQL, visualization tools
Work EnvironmentResearch-focused, economic modeling, data interpretationBusiness insights, reporting, dashboard creation
Industry UsageFinance, consulting, government, research institutionsMarketing, finance, tech companies

Internship Data Science Economics typically involves economic modeling, statistical analysis, and programming skills, often in research or policy environments. Data Analyst Internships focus on interpreting data to generate business insights, using tools like Excel and SQL. Both roles require analytical skills but differ in focus and industry applications.

What are popular job titles related to Internship Data Science Economics jobs in Washington?

For Internship Data Science Economics jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Internship Data Science Economics jobs in Washington look for?

The top searched job categories for Internship Data Science Economics jobs in Washington are:

Infographic showing various Internship Data Science Economics job openings in Washington as of August 2026, with employment types broken down into 26% Internship, and 74% Full Time. Highlights an 100% In-person job distribution.

Computational Economics Expert/Sr. Computational Economics Expert- (Contractual) - ITDDP

Imf

Washington, DC

$104K - $131K/yr

Full-time

Posted 13 days ago


Job description

Work for the IMF. Work for the World.

Under the direction of the Section Chief (Data Science Section) in the IT Department at the IMF, the Computational Economics Expert provides Fund-wide services on Computational Economics using computer-based economic, econometric and machine learning modeling for the solution of economic problems related to the Fund's business capabilities of surveillance, lending, and capacity development.


The role requires combinations of strong Computer Science and Economics skills to provide efficient and integrated solutions to the business, not only on the technological dimension, but also on the economic and quantitative modeling dimensions. Additionally, developing and delivering training on use of economic, econometric and machine learning modeling techniques and software, and advising on mathematical and high performance computational related problems are integral parts of the role.
This position requires advanced programming skills and knowledge of or experience with Economic and Econometric Modeling.


Major Duties and Responsibilities

  • Collaborates with economists, financial sector specialists, and other professionals from the line-of-business in the selection of the appropriate methods and data sets for economic and econometric modeling.
  • Develops and implements advanced economic and econometric models.
  • Undertakes research towards crafting solutions for challenges arising from economic and econometric modeling.
  • Analyzes requests, designs methodology and develops programs and modules for advanced economic and econometric models.
  • Researches, analyzes, and develops algorithms to improve the performance and extend the capabilities of economic and econometric models, including optimization for parallel computing environments and large-scale simulations, as well as improving I/O efficiency in high-throughput data workflows.
  • Writes computational and data processing programs using high-level programming languages such as Matlab, Python, R, etc., including development and maintenance of reusable internal libraries and packages, implementation of standardized data access and reporting frameworks, and application of automated testing, documentation, and code quality assurance practices.
  • Supports the operation and continuous improvement of shared computational environments and software stacks, including contributions to system configuration, package management practices, and governance of analytical tools and resources, as needed to enable reproducible and efficient research workflows.
  • Develops course materials and provides training on use of economic and econometric modeling techniques.
  • Follows up current academic research on computational economics, applied mathematics and econometrics.

Minimum Qualifications

Advanced degree in Computer Science, Economics, Engineering, Applied Mathematics, or relevant field plus a minimum of four (4) years of post-graduation professional experience, or a bachelor's degree plus a minimum of ten (10) years of post-graduation professional experience is required. Additionally, below required competencies are required for this role:


1. Economic and Econometric Modeling Expertise

  • Knowledge and experience with economic and econometric models including time series, cross-section, panel data econometrics, and macroeconomic models (DSGE, HANK, ABM).
  • Proficiency in quantitative modeling, statistical estimation methods (maximum likelihood, method of moments, Bayesian inference, VAR), and use of econometric/statistical software (EViews, Stata, Matlab, Julia).
  • Ability to develop problem definitions, models, and constraints from informal requirements, managing ambiguity and competing objectives.

2. Mathematical, Numerical, and Optimization Methods

  • Expert knowledge of numerical methods, linear algebra, large-scale mathematical programming, and algorithm development.
  • Strong understanding of optimization techniques including linear, nonlinear, dynamic programming, simulation-based optimization, stochastic programming, robust optimization, and approximate dynamic programming.
  • Familiarity with computational complexity theory and applied/theoretical statistical learning.

3. Advanced Programming and Computational Skills

  • Advanced programming skills in scientific computing and data science languages such as Matlab, Python, and R.
  • Extensive experience with distributed and parallel computing.
  • Knowledge of machine learning algorithms, including deep learning.
  • Understanding of personal computer architecture and memory organization.
  • Ability to follow current academic research in computational economics, applied mathematics, and statistics.
  • Strong oral and written communication skills and ability to convey higher level technical concepts to non-experts.

This is a one-year contractual appointment. Contractual appointments at the IMF are renewable for up to four years of cumulative contractual service, pending incumbent's performance, budget availability, and continuous business need.

Department:

ITDDPDS Information Technology Department Data Platform Division Data Science Section

Hiring For:

A11, A12

The IMF is guided by the principle that the employment, classification, promotion, and assignment of staff shall be made without discrimination against any person. We welcome requests for reasonable accommodations for disabilities during the selection process. Information on how to request accommodations will be provided during the application process.