Finding a new career in data beyond international development

This post is a bit adjacent to data visualization, written in response to questions from colleagues impacted by the USAID stop work order finding themselves unexpectedly looking for new roles when companies across our sector are doing mass layoffs and furloughs. If you’re in that position looking for ideas on pivoting outside of development, this is for you.


Data professionals are uniquely positioned to pivot to roles in adjacent sectors, private sector companies and consulting.

I made that leap myself back in 2017, when I left JSI and joined Excella, a tech consulting firm based in Arlington. I started as the Data Visualization Capability Lead and left as the Acting Director of AI and Analytics, when I decided to move into independent consulting to focus on projects and teaching at the intersection of data visualization and public health.

If you were in a role that falls within any of the following you likely have some of the necessary skills to seek data-related opportunities in a new sector:

  • Monitoring, evaluation, research, and learning

  • Health information systems

  • Data systems and web development

  • Data analytics

  • Strategic information

When I was working in consulting, we had major projects with private sector and government clients designing software, building data systems, and developing data visualization and analytics tools (among other things).

We typically thought about data roles as falling into four big areas, outlined below, which I still think is a helpful framework for considering the different types of data roles out there.

Four Domains of Data Expertise

Data engineering

What it is: Focused on organizing and curating data sources often focusing on automation. Builds and maintains data warehouses, data lakes, and other repositories. Knows languages like SQL and Python, and familiar with common data platforms like AWS, Azure, Databricks, and more

International development parallels: People who build and managed the back end of health or logistics information systems, or managed the data repositories for digital health applications

Data analysis

What it is: Answers questions with data, often looking to multiple sources for insight. Conducts exploratory data analysis to identify patterns in large datasets. Likely knows a good amount of stats to be able to estimate margins of error and other nuances. May use a wide range of tools depending on the company or industry including R, python, Tableau or PowerBI (more as dashboard users than developers), or Excel

International development parallels: Monitoring and evaluation team members responsible for collecting and reporting on program performance; researchers

Data visualization

Creates charts, graphics, dashboards, and/or interactive data stories to communicate information to a wide range of stakeholders. Has skills both in analytics and design, with a foundational knowledge of best practices in visualization design. Wide range of sectors and opportunities, from BI roles to data journalism. Tools used include:

  • For static charts, R/ggplot, Excel, Canva, Illustrator, Figma, or other design software.

  • For interactive charts, Flourish, Datawrapper, D3, or other code-based libraries.

  • For dashboards, may use Tableau, PowerBI, Qlik, or other interactive platforms.

International development parallels: Dashboard developers working on health information systems or internal project monitoring dashboards; graphic designers who craft infographics or charts for project reports

Data science

What it is: Uses advanced analytics and AI to explore massive volumes of information, find patterns, and work with unstructured data. Likely knows Python and can build models.

International development parallels: Advanced analytics and stats roles often within informatics or tech teams

Making the pivot

Often, people have deep expertise in one of these four data domains, but can speak the language of the others. There are also a lot of related skills and knowledge that can help position you for a new data role, including:

  • Understanding software development structures and tools - these could include Agile principles, experience using planning tools like Confluence or JIRA, or even learning some basic coding capabilities if you have ambitions of doing more in data engineering or interactive data visualization

  • User centered design, including how to test, fix, and iterate when designing an information system or data visualization product

  • Change management and communications - don’t underestimate the value and importance of supporting the use of whatever data tools you’re building

Looking for data roles that are in similarly mission-focused areas, consider:

  • State and county government, including departments of public health

  • Local and national nonprofits - if you want to work on data team, a larger organization is more likely to have that opportunity while smaller orgs might rely on a solo ‘data person’ which can be challenging if you’re pivoting to a new role

  • Think tanks like Kaiser Family Foundation, Brookings Institute, and others - if it’s a place that publishes analysis and reports that you find useful, they often have a team responsible for that analysis work

  • Consulting firms with a diverse range of clients, which could afford the opportunity to learn from the private sector on one assignment and also have some mission driven work with other clients down the road

One of the biggest challenges in navigating data opportunities is the wide range of different titles given to what could be the same role, and the same title meaning a wide range of different things depending on the company.

In data visualization, the field I’m most connected with, you can browse the Data Viz Society Jobs Board for examples (and current openings) for data viz roles. You may also find the resources in the 2024 State of the Data Viz Industry report (useful for seeing patterns and trends in the broader industry including the use of AI tools in data viz) and our Career Paths in Data Viz Report. A while back, I also mapped out five questions I would ask if I was starting out in a data viz consulting role which are still useful today.

Three questions to ask in your pivot

I’ll close the the reflection that a career shift likely means rethinking three key things:

  • What other topics or sectors are you interested in or passionate about? It may be hard to imagine not being in the international development community, but think bigger - what about the work you were doing did you value? What parts of your day or week brought you the most joy? If working with beneficiaries was important, then consider looking for local nonprofits to apply your skills; if instead you loved the challenge of building improved information systems for governments, consider how you could do the same for clients in a consulting firm.

  • What skills do you have that are sector agnostic? Yes, your subject matter expertise (whether in global health, food security, logistics, or something else) matters and adds value. But this is a time to focus on transferable skills - and that’s where skills in data science, data analysis, data visualization, and data engineering can be hugely helpful in making that shift.

  • What additional skills or certifications do you need to be competitive in a different sector? While you may have accumulated a lot of certificates from workshops and trainings during your time working in development, consider other options. If you want to keep working in tech, consider agile certifications that will help you learn the ‘language’ of the industry and a future team. There are many virtual learning opportunities that will help ease the transition without the time and cost burden of an additional university degree. I know that an MPH almost felt like an ‘entry level’ requirement for a lot of development jobs, but didn’t find that to be the case when I was working in tech consulting.

Many of the people in international development are making a forced pivot, which hurts the heart in its own way. But there are so many opportunities out here, and I know that any data team is stronger with the passionate, dedicated professionals I’ve had the privilege to work with throughout my time working in global health.

Resource links

Data Visualization Society

Data Viz Society Jobs Board

Data Viz Society State of the Industry Survey 2024

Data Viz Society Career Paths Report and Interview Series

Five Questions to Ask When Starting in a Data Viz Consulting Role

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