Data Analytics Intern, Office of Audit and Investigation Services (Remote)

Contribute to data-driven projects and enhance analytics in oversight activities.

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UNFPA - United Nations Population Fund

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Application deadline 9 months ago: Sunday 31 Aug 2025 at 23:59 UTC

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Overview

Contribute to data-driven projects and enhance analytics in oversight activities.

You have:

  • Be enrolled in a postgraduate degree programme in Data Science, Computer Science, or a related field.
  • Be enrolled in the final academic year of a first university degree programme in Data Science, Computer Science, or a related field.
  • Have graduated with a university degree in Data Science, Computer Science, or a related field and start the internship within one-year of graduation.
  • Knowledge of data models, database design, ETL design and development, and data mining.
  • Advanced programming skills with Python focused on data engineering, data analysis, and machine learning.
  • Familiarity with statistical methods such as regression, distribution properties, and hypothesis testing.
  • Experience with Microsoft Power BI is highly desirable.
  • Fluency in English required, with proven ability to express well verbally and in writing.
  • Good knowledge of one of the other UN official languages is desirable.

Contract

This is a Internship contract. It usually requires 0 years of experience, depending on education. More about Internship contracts.

Location: Remote Full/Part time: Full-Time Duration: 24 weeks

How you can make a difference: UNFPA is the lead UN agency for delivering a world where every pregnancy is wanted, every childbirth is safe and every young person's potential is fulfilled. UNFPA’s strategic plan (2022-2025), reaffirms the relevance of the current strategic direction of UNFPA and focusses on three transformative results: to end preventable maternal deaths; end unmet need for family planning; and end gender-based violence and harmful practices. These results capture our strategic commitments on accelerating progress towards realizing the ICPD and SDGs in the Decade of Action leading up to 2030.

The Office of Audit and Investigation Services (OAIS) is an operationally independent office at UNFPA and reports to the Executive Director of UNFPA. The Office is responsible for supporting the achievement of the objectives of UNFPA by contributing to the improvement of its operations, risk management and results through its internal audit, investigation, and advisory services. OAIS is composed of the Office of the Director, an Internal Audit Branch and an Investigation Branch.

The Position: The Office of Audit and Investigation Services is offering an internship opportunity to a Data and Analytics student or graduate (see education requirements) to contribute to ongoing projects and initiatives aiming at enhancing the use of modern analytics technologies in oversight activities. These initiatives are in the domains of data engineering and data science, including the design and implementation of machine learning models.

Job Purpose: The interns will work under the overall guidance of the Director of OAIS and the direct supervision of the Data Management Specialist, supporting projects aimed at integrating data-driven methods into the oversight function.

Responsibilities:

The intern will contribute to the following tasks: • Collaborate with audit teams to define and document data requirements. • Support the identification and extraction of data from operational systems (e.g., Oracle ERP). • Assist in the design and implementation of data pipelines and ETL processes. • Develop scripts for data analysis and automate data validation routines. • Conduct exploratory data analysis and statistical hypothesis testing. • Design and implement interactive dashboards and visualizations. • Study, design, and implement machine learning models for risk assessment and anomaly detection. • Support the development of LLM-based solutions to facilitate AI integration in oversight activities.

Qualifications and Experience:

All interns must meet the following educational and other eligibility requirements:

Education: • Be enrolled in a postgraduate degree programme (such as master’s programme or higher) in Data Science, Computer Science, Computer Engineering, Information Management, Statistics, Mathematics, or a related field; • Be enrolled in the final academic year of a first university degree programme (minimum Bachelor’s level or equivalent) in Data Science, Computer Science, Computer Engineering, Information Management, Statistics, Mathematics, or a related field; or • Have graduated with a university degree in Data Science, Computer Science, Computer Engineering, Information Management, Statistics, Mathematics, or a related field and, if selected, must start the internship within one-year of graduation.

Knowledge and Experience: • Knowledge of data models, database design and development, ETL design and implementation, data mining. • Advanced programming skills with Python focused on data engineering, data analysis, and machine learning. • Familiarity with statistical methods such as regression, distribution properties, and hypothesis testing. • Experience with Microsoft Power BI is highly desirable.

Languages: • Fluency in English required, with proven ability to express well verbally and in writing. • Good knowledge of one of the other UN official languages (French, Arabic, Chinese, Spanish or Russian), is desirable but not a requirement.

Learning Elements: By the end of the internship, interns can expect to gain: • A deeper understanding of the role of internal oversight within UNFPA. • Familiarity with UN policies and procedures related to accountability, ethics, and governance. • Hands-on experience with data analytics in oversight, particularly in development and humanitarian contexts. • Exposure to collaborative work in a multicultural, multidisciplinary team environment.

Required Competencies: • Demonstrates integrity; • Demonstrates the ability to remain objective, neutral, and independent; • Displays cultural sensitivity; • Produces timely, quality outputs; • Exercises sound judgment/analysis; • Ability to handle multiple tasks; • Writes clearly and effectively; and • Speaks clearly and convincingly.

Financial Aspects: Interns do not receive a salary or any other form of remuneration from UNFPA. The costs associated with an intern's participation in the programme must be assumed either by the nominating institution, which may provide the required financial assistance to its students, or by the students themselves, who will have to meet living expenses as well as make their own arrangements for accommodation, travel and other requirements. However, they receive a stipend to help cover basic daily expenses related to the internship, if not financially supported by any institution or programme, such as a university, government, foundation, or scholarship programme. The amount of the stipend varies according to the intern’s agreed place of work, which may be different from the duty station of the hiring office in cases of remote arrangements. In addition, applicants must have medical insurance for the duration of the internship. Proof of insurance will need to be submitted before the internship begins. UNFPA does not provide medical insurance for interns.

How to apply: An application letter which states the candidate’s motivation to apply for this internship as well as a curriculum vitae/resume. All documents must be sent by e-mail with subject “Application OAIS/DATA Intern” to DirectorOAIS@unfpa.org by midnight on 31 August 2025 (EST).

Disclaimer: UNFPA does not charge any application, processing, training, interviewing, testing or other fee in connection with the application or recruitment process. Fraudulent notices, letters or offers may be submitted to the UNFPA fraud hotline:

https://web2.unfpa.org/help/hotline.cfm 

Potential interview questions

Describe a project where you used data analysis to solve a problem. What approach did you take? We want to understand your practical experience and problem-solving abilities in data analysis. Discuss your specific role, the tools you used, and the impact of your work.
How do you ensure data quality in your analysis? This assesses your understanding of data integrity and validation techniques. Pro members can see the explanation.
Can you give an example of a machine learning project you've worked on? What were the results? Pro members can see the explanation. Pro members can see the explanation.
How do you approach learning a new programming language or tool? Pro members can see the explanation. Pro members can see the explanation.
Discuss a time when you collaborated with a team on a data project. What role did you play? Pro members can see the explanation. Pro members can see the explanation.
What methods do you use for exploratory data analysis? Pro members can see the explanation. Pro members can see the explanation.
How would you design an interactive dashboard for a data set? What key elements would you include? Pro members can see the explanation. Pro members can see the explanation.
Describe a situation where you had to handle multiple tasks at once. How did you manage them? Pro members can see the explanation. Pro members can see the explanation.
Added 9 months ago - Updated 9 months ago - Source: unfpa.org