Displacement Tracking Matrix (DTM) South Sudan Analytics, Knowledge and Output (AKO) Quality Intern

Thematic focus: Working across multiple datasets collected by DTM in South Sudan to ensure data quality and support with analysis and reporting aimed at informing humanitarian, early recovery and public health planning. Automating data cleaning, analysis and visualisation through development of suitable R scripts.
Reporting directly
DTM Data Analyst (Juba, South Sudan) & AKO Unit Lead (London)
Overall supervision
Global DTM Coordinator (London)
Thematic supervision
DTM Coordinator (Juba, South Sudan)
Duty Station
London, UK
Number of positions
Closing Date
Starting Date
As soon as possible
6 months with possibility of extension



Since 2004 the Displacement Tracking Matrix (DTM) is IOM’s main operational tool for tracking and monitoring the movements and the evolving needs of displaced populations. It has been systematically deployed in medium to large-scale humanitarian response operations in the last seven years, including in all Level 3 emergencies. During 2019 DTM was active in over 78 countries. To coordinate and support operations implemented by approximately 5,200 staff, the global DTM support team is comprised of 45 specialists across eight locations (Geneva, London, Bangkok, Nairobi, Dakar, Cairo, Vienna and The Hague).

The DTM team in South Sudan is one of the world’s largest, with over 80 staff working across multiple components and thematic areas to inform humanitarian, early recovery and public health programming. Ongoing operations include tracking displaced and returned populations and their needs, monitoring population flows through key border crossings and transport hubs, operating biometric registration systems for fair and efficient delivery of humanitarian aid, delivering thematic household surveys in urban areas and displacement camps, and assessing existing infrastructure and services in areas of return.
Following a scale up of DTM’s operations in South Sudan since 2018, there is now an unprecedented amount of data available for analysis. However, such data is only beginning to be leveraged at its maximum potential for the purpose of guiding humanitarian, early recovery and public health interventions. The unit is currently expanding its data analysis portfolio, developing collaborations with other humanitarian and early recovery partners and expanding beyond descriptive analysis while maintaining a large range of regular information products accessible by operational partners. It is also transitioning towards progressive automation of data analysis processes, following global best practices in data analytics and data protection.

The main objective of this internship will be to assist IOM to develop new analytical products based on data collected by DTM in South Sudan, with a particular focus on location assessment and household / individual survey data, and to contribute to the automation of data cleaning, analysis and visualisation processes by developing suitable scripts in R.

Located in the IOM London office, under direct supervision of the DTM Analytics, Knowledge and Output Quality (AKO) Unit Lead (London), DTM Data Analyst (Juba, South Sudan) and the DTM Coordinator (Juba, South Sudan), and the overall/daily supervision of the Global DTM Coordinator (London), the successful candidate will integrate into the AKO unit.




Objective: Technical assistance in the production and review of information products and reports based on DTM and other data, with the aim of informing humanitarian, early recovery and public health programming in South Sudan. Development of R scripts for data cleaning, analysis and visualisation. It is expected that the intern will spend approximately 80% of their time supporting the DTM team in South Sudan.

Common to all interns in the AKO unit:

  • Provide support in analysis and interpretation of data, as tasked by the DTM unit, with a primary focus on South Sudan;
  • Facilitate the logistical organization of webinars in support of the DTM unit to ensure regular internal and external updates on human mobility and displacement;
  • If necessary, in coordination with DTM South Sudan provide updates on human mobility trends, changes and any other significant observations surrounding human mobility and displacement in South Sudan;
  • Assist the DTM South Sudan and teams in London in the production and quality control of documents;
  • Coordinate with other units of the global DTM support team to ensure continuity of functional workflows;
  • Provide administrative and logistical support to the London team when needed with a primary focus on South Sudan;

Thematic focus: Support DTM South Sudan data analysis and reporting, automating data cleaning, analysis and visualisation through development of suitable R scripts.

  • Develop R scripts for data cleaning, analysis and visualization of data collected by DTM in South Sudan, with a focus on location assessments and household/individual surveys;
  • Provide support in analysis and interpretation of data as well as in review of DTM documents requiring remote assistance, with a primary focus on South Sudan;
  • Draft and edit reports, dashboards and infographics presenting analysis of data collected by DTM in South Sudan, ensuring the products are accessible to non-technical audiences;
  • Identify and synthesize relevant secondary data sources, contextualizing DTM data to inform humanitarian, early recovering and public health programming;
  • Assist in the refinement of DTM’s data collection methodologies and questionnaires, identifying good practices and providing recommendations for improvement;
  • Support technical training of other staff, including through the organization of dedicated webinars;
  • Support any reporting activities related to DTM’s work in South Sudan;
  • Perform other duties as may be assigned throughout the internship. 




The incumbent is expected to demonstrate the following competencies:

Excellent research, writing, communication and statistical/analytical skills; ability to prepare clear and concise reports; Accountability; Client Orientation; Continuous Learning; Communication; Creativity and Initiative; Planning and Organizing; Professionalism -  displays mastery of subject matter; incorporates gender related needs, perspectives, concerns and promotes equal gender participation; Technological Awareness.



Strong and demonstrable knowledge and interest in migration, development economics, political economy of development, conflict studies, public health and/or humanitarian issues; personal commitment, efficiency, flexibility; ability to work effectively and harmoniously in a team and with colleagues from varied cultures and professional backgrounds under tight deadlines.


  • Proficiency using Microsoft Office 365 (Excel, Word and PowerPoint)
  • Experience working with R (programming language), including at least three of the following packages: dplyr, data.table, ggplot2, shiny, sf (or equivalent)
  • Experience in quantitative research methods (statistical modelling, applied econometrics and/or machine learning)


  • Experience using Adobe Suite (e.g. InDesign, Illustrator)
  • Experience with GIS software such as ArcGIS/QGIS
  • Experience with other coding languages (e.g. Python) and relational databases (inc. SQL)
  • Experience in qualitative research methods




Master’s degree from an accredited academic institution in a field of study related to Economics / Development Economics, Data Science, Political Science, Social Science, Development Studies, Public health, Epidemiology or other relevant disciplines with a significant quantitative component. Alternatively, a Bachelor’s degrees with 2 years of relevant working experience.




Required: Excellent communication skills in English (written and oral).Advantegeous: Working knowledge of Arabic and/or additional UN language.   HOW TO APPLY Interested candidates must submit updated CV and cover letter (in PDF format and only one file with your name and surname) to dtmrecruitment@iom.int adding Displacement Tracking Matrix (DTM) South Sudan Analytics, Knowledge and Output (AKO) Quality Intern in the subject line, no later than Thursday 25th June. NOTE: Only shortlisted candidates will be contacted. Incomplete applications or submitted in more than one file (CV+cover letter in PDF format) will not be considered.