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UNPAID INTERNSHIPS WITH OFFICE OF TRADE AND ECONOMIC ANALYSIS IN THE COMMERCE DEPARTMENT’S INTERNATIONAL TRADE ADMINISTRATION

 

OTEA MISSION:

The Office of Trade and Economic Analysis (OTEA) is seeking unpaid interns on a part-time basis. OTEA combines advanced analytics with modern data methods and tools to supports U.S. competitiveness and provide actionable insights into U.S. trade, domestic economy, and security matters. 

In OTEA, you will be working alongside the Data Analysis and Quantitative Analysis Teams to provide data-driven expertise and insights. The Data Analysis Team publishes internal and public-facing data products and conducts cross-sectoral analytics. The Quantitative Analysis team uses econometric tools and models to rigorously analyze the impact of policies, actions, and events on the United States and global economies. 

 

You MUST be a US citizen to apply for this internship.

This is a IN-PERSON, HYBRID, or REMOTE internship.

This internship can be sponsored for academic credit.

 

DUTIES MAY INCLUDE:

Interns are to be assigned to special projects that support OTEA’s big data environment and the use of open-source, internal, and commercial trade and economic datasets. Project assignments are made collaboratively: interns will discuss interests and technical strengths with the team and will be matched to one or more defined projects based on office priorities. Interns are expected to deliver well-documented code, reproducible workflows, and reusable outputs suitable for handoff and ongoing maintenance. 

 

Across projects, common responsibilities may include:

  • Build and run cloud-based data pipelines in AWS and/or Google Cloud to ingest, transform, validate, and publish datasets including in the areas of trade and supply-chains. 
  • Write and optimize SQL and Python for data wrangling, joins across sources, and scalable aggregations (e.g., Harmonized System codes, countries, descriptions, time).
  • Integrate open-source and commercial data; create or leverage reproducible methods and reference mappings (e.g., HS/HTS, ISO country codes, company identifiers/names, time periods) and maintain data dictionaries and metadata.
  • Implement data quality checks (freshness, row counts, null rates, duplication, reconciliation to known totals) and produce repeatable, quality-assured outputs.
  • As applicable, apply statistical and/or economic modeling concepts (exposure indices, concentration/dependency measures, policy-shock before/after frameworks, transfer/diversion metrics) to produce analysis-ready measures.
  • Develop NLP pipelines to extract structured fields (entities, measures, dates, locations, products) from both clean and messy text; evaluate performance on a labeled sample.
  • Conduct data science research using statistical and analytical tools to analyze complex datasets and test hypotheses using rigorous, reproducible methods.
  • Build automated workflows (including agentic processes where appropriate) for data gathering and anomaly detection.
  • Design and build pilot and demonstration applications, including interactive prototypes and internal tools (e.g., dashboards, Tableau/Power BI visuals, and lightweight web apps using JavaScript/React) and provide recommendations to management on feasibility, scalability, and pathways to operational adoption.
  • Produce repeatable visual outputs (tables, charts, dashboards) that refresh from the big data environment.

 

IDEAL APPLICANTS: 

The ideal candidate is a technically proficient graduate student (or advanced undergraduate) with strong analytical skills, the ability to work independently, and a demonstrated interest in applying data science and/or economic modeling to U.S. competitiveness questions, including in the areas of trade and supply chains. Upper-level undergraduates with exceptional relevant technical experience may also apply.

Candidates must demonstrate technical proficiency in data science, data analytics, or programming. Experience working with large datasets and building repeatable workflows (e.g., scripts, notebooks, or data pipelines) is required. 

Experience with one or more of the following is highly desirable: SQL and Python development; use of cloud platforms such as AWS and/or Google Cloud; data engineering concepts (ETL/ELT, data validation, logging, versioning); data visualization tools (e.g., Power BI/Tableau or Python/R libraries); and statistical/economic tools. 

Beneficial experience includes domain knowledge in economics and past work using open-source and/or commercial datasets relevant to international goods and services trade, firm, or supply chain analysis.

 

REQUIREMENTS:

Applicants must be U.S. citizens and enrolled in an accredited U.S. college or university. Candidates must be able to commit 10+ hours per week* for 16 weeks. Duration may be extended as needed/available for special projects. These positions are unpaid.

*Internship hours and dates are flexible, and accommodation can be made for class schedule. 

For remote candidates, interns must be capable of working remotely and have reliable computer and internet access.

 

HOW TO APPLY:
We are seeking candidates with immediate availability. Interested applicants are asked to apply by emailing ONE document containing a 1-page cover letter and 1-page resume (U.S. citizenship must be noted on the resume for consideration) DIRECTLY to amanda.reynolds@trade.gov, eak.gautam@trade.gov, and eric.baran@trade.gov. Please include “Intern Application to OTEA” in the email header. In the cover letter, please include your expected dates and hours of availability. Submit your application by 11:59pm EST on January 28, 2026. Applications will be reviewed as they are received and on a rolling basis, so submission before the deadline is highly encouraged. Thank you for your interest!