Data Scientist, MNO Data

What if the most effective way to fight poverty was also the simplest: give people money and trust them to decide what they need?

Since 2011, GiveDirectly has proven that idea at scale. We’ve delivered more than $1B in cash directly to 2+ million people living in poverty and crisis across 15 countries, and rigorous research shows the results: healthier kids, stronger businesses, sturdier homes, and more resilient families and local economies. Cash is now widely recognized as one of the most scalable, cost-effective, and dignified forms of aid.

Our ambition goes beyond our own programs. We want cash to become the benchmark for aid, much as the index fund became the benchmark for investing, so that every aid dollar is held to one question: is this doing more good than giving the money directly to people living in poverty?

We’re growing fast, and this is a rare and important moment to join.

We expect to hit $1B in revenue in 2026 with significant growth forecast for 2027. At the same time we are building a new technology stack and operating model designed for a roughly 10x change in scale, and we are actively pursuing partnerships with major funders to move even more money in bigger ways, to people who need it. We are known for our extensive integration of technology into field processes; our quantitative approach to performance measurement; and our commitment to rigorous, independent, experimental evaluation of our impact, with multiple Randomized Control Trials completed and others in progress.

• Improve and extend our library of analytical method templates for establishing where people live from MNO data, and depending on circumstances, for detecting displacement or estimating poverty. Design novel methods when an intervention requires it.
• Support colleagues in technical conversations with operators, bringing clarity on the data we need and why, and steering discussions toward technical designs that make the analysis workable.
• Assess the information that can be inferred from each operator's data given data types and sparsity, and for each geography and targeted area. Support intervention design to account for data quality.
• Write tests and method specifications for MNO data engineers to implement: steps, parameters, pseudocode, validation criteria.
• Guide operator engineering teams through implementation, in writing and in person. Adapt methods to accommodate large data volume and computational constraints, balancing accuracy and operational needs.
• Run in-country workshops with operators to support the set-up of new analyses and - where feasible - tune parameters based on statistical tests and distributions.
• Feed every new analytical and implementation element back into standard templates, so the next country or intervention starts from a better position than the last.
• Design for privacy from the start, so that as little data as possible has to be shared: aggregation, minimization, and where useful, privacy-enhancing technologies such as private set intersection or homomorphic encryption.
• Protect the confidentiality of what operators share with us and improve internal data security processes and tools as we grow.
• Build internal training material so that our technical and non-technical teams understand the strengths and limits of this data, and design interventions accordingly.

• Exceptional alignment with GiveDirectly Values and active demonstration of our core competencies: emotional intelligence, problem solving, project management, follow-through, and fostering inclusivity. We welcome and strongly encourage applications from candidates who have personal or professional experience in the low-income and/or historically marginalized communities that we serve.
• Strong mathematical modeling, machine learning and statistics. You choose methods for the question rather than for their sophistication, and you value being able to explain a result over squeezing out the last point of performance.
• Deep comfort with spatio-temporal data: temporal filtering, GIS, probability distributions, combinatorial reasoning, and working with sparse, irregular observations. Direct experience with Call Detail Records (CDRs) or latching data is a strong plus. Comparable experience with mobility, transport, sensor or remote-sensing data counts.
• The ability to reason without ground truth. Much of this work has no validated answer to check against, and you're comfortable setting parameters by reading the shape of the data and defending that choice.
• Pragmatism about the trade-off between accuracy and implementability. You've deliberately simplified a method to fit an operational constraint, and you can say what it cost you.
• Excellent communication and relationship-building skills. You can explain a method and its limitations to an operator's engineers, to their data protection officer, to their leadership and to colleagues with or without technical background. You write well and are comfortable presenting to these multiple audiences. You build trust with counterparts you don’t manage, and they want to work with you again.
• Experience writing technical specifications that other teams implemented, clear enough that people you don't manage could follow them correctly.
• Able to read and review SQL and Python written by others, and to find the logical error in someone else's query. Writing production-quality code yourself is welcome but not required. Enough understanding of large data volumes and databases to judge when analytical simplification is required.
• Commitment to privacy by design as a foundational value and starting point rather than a compliance step: designing analyses so that less personal data has to be shared. Familiarity with privacy-enhancing technologies for shared computation (private set intersection, secure multi-party computation, homomorphic encryption) is a strong plus.
• Commitment to confidentiality. You've handled a partner's commercially sensitive data and can describe the habits you built around it, not just the clause you signed.
• Experience designing training material that changed how non-specialist colleagues used a data source.
• Comfort in fast-moving contexts where the brief may often shift, and where your technical expertise and understanding may not be shared by other stakeholders.
• Additional desirable experience may include: poverty modeling; familiarity with survey data and survey instruments; experience inside a mobile network operator or working closely with one; open-source contributions in the mobility estimation space.
• Comfortable with travel to fragile and post-disaster contexts.
• Language Requirement: English.
• Language Preferences: French, Portuguese, Swahili or Spanish.

Our team spans 20+ countries and 69 languages. Our culture is candid, analytical, and non-hierarchical. We expect high ownership and give people real responsibility early. Our values are central to how we hire, work, and grow, and they are deliberately opinionated:

• Recipients first. Recipients’ preferences come before those of donors or ourselves.
• Team next. We optimize for organizational success, not individual success.
• Be proactively candid. We say what we believe and share information openly.
• Create positive energy. We aim to be a source of energy for colleagues, not a drain.
• Think rigorously; act quickly. We reason from first principles, then act rather than debate.
• Know yourself and grow. We own our imperfections and seek feedback to grow.
• Accept reality. Propose solutions. We focus on what can change and bring solutions, not just problems.
• Be productively ambitious. We take risks for step-change impact, not incremental progress.

If they describe how you like to work and they energize you, this could be a great fit.

Want to learn more? Read and listen:

We are one of Time100’s Most Influential Companies of 2026, and our work has been covered by The Economist, NPR, TED, and The Washington Post. We're now preparing to deliver billions of dollars a year to people in extreme poverty, if funding allows. Read our CEO's essay on what that will take.

GiveDirectly gives cash directly to people living in poverty and in emergencies. Both depend on the same question: did this person live in this place, at this time? We ask it when we target the poorest households, and when a disaster displaces a community overnight. Location records held by Mobile Network Operators (MNO) can help us estimate an answer to this question at scale. We work with MNOs so they can infer, from their own records, whether a subscriber was resident in a target area over a defined period. Robust residence location inference from MNO data requires in-depth analytical work, and the methods we design have to run on an operator's systems - most often implemented by their engineers - under strict data protection and confidentiality rules.

We are hiring a Senior Data Scientist to progress our work on location inference from MNO data, and to make it repeatable. Your job is to improve and extend our library of method templates, adapt them to each new operator and setting, and design new elements when an intervention requires it. You'll assess what can be inferred from a given operator's data, specify the analysis clearly enough for their data engineers to implement, then test it with them remotely or on site. You'll support introductory meetings with MNOs, describing methodologies at a high level, and inform the work of data privacy and cybersecurity teams to ensure only necessary data are shared securely. You'll also help colleagues across GiveDirectly understand the strengths and limitations of this data source, so we design programs around questions it can best answer.

This work is live in several countries, and we're expanding it across the countries where we have offices and to low- and middle-income countries anywhere in the world when a crisis hits.

Reports to: Senior Product Manager - MNO data

Level: Senior Manager

Location: At this stage of GiveDirectly’s growth and scale, we’re prioritizing hiring in the countries below, where we can employ you through a GD entity or an established employer of record: Cameroon, Canada, Colombia, DRC, Germany, Ghana, Kenya, Malawi, Mozambique, Netherlands, Nigeria, Poland, Portugal, Rwanda, South Africa, Spain, Turkey, Uganda, United Kingdom, and United States. This list reflects where our employment infrastructure is established today, and may evolve as we grow. If you’re based elsewhere and not open to relocation, we may not be able to consider your application for this role right now, but we’d encourage you to check back. Please note that we are unable to sponsor or take over sponsorship of employment Visas in the U.S. or U.K. at this time.

Travel Requirement: Substantial international travel, roughly 25 to 50% of your time depending on emergencies, sometimes at short notice - for workshops with operators to support programs and emergency responses.

At GiveDirectly, we strive to pay our employees generously and equitably. We use an accredited third party salary aggregator to calculate what we believe to be competitive pay based on role, location, and cost of living. We also have a no negotiation policy to ensure we are paying staff equitably across roles. Read more about our compensation philosophy here.

Unless otherwise noted, the benefits stipend may be used to cover benefits or taken as additional taxable income.

United State

• Base Salary: $107,070
• Bonus at Target Performance: 10%
• Annual Benefits Stipend: $21,393

United Kingdom

• Base Salary: £70,250
• Bonus at Target Performance: 10%
• Annual Benefits Stipend: £2,760

Kenya

• Base Salary: $72,550
• Bonus at Target Performance: 10%
• Annual Benefits Stipend: $8,454

This role is fully remote, so if you are not based in the US, UK or Kenya, we will share an estimated salary benchmark for the country you are based in during the hiring process.

GiveDirectly is an Equal Opportunity Employer. All qualified applicants are considered for employment without regard to the person’s race, color, religion, national origin, sex, sexual orientation, age, marital status, veteran status, disability, or any other characteristic protected by applicable law.

Flagging for US applicants: We invite you to «Know Your Rights» as an applicant.

Commitment to Safeguarding

As a global organization working with communities to eliminate extreme poverty, GiveDirectly takes the safeguarding of its recipients, staff, and partners seriously. To that end, GiveDirectly is a member of the Misconduct Disclosure Scheme, and will systematically check with previous employers about any abuse or misconduct related matters involving potential new hires. We may also employ other robust pre-hire screens, including in-depth reference checks, criminal background checks, and sanctions screens.

These efforts help us continue to build and maintain trust with the communities we work with, and prevent abuse to our recipients and staff.

• *GD is committed to observing all local, national and international laws that protect people and basic human rights of all. GD is committed to a policy of “zero tolerance when it comes to preventing, reporting, or responding to any form of abuse or exploitation.” and expects anyone who works for GD to uphold the protection and safeguarding of our recipients as a priority.**

Reasonable Accommodations

We are committed to fostering an inclusive and accessible work environment. If you require any accommodations during the application or interview process, or to perform the essential functions of the role, please email us at careers@givedirectly.org with the email subject “Accommodation Needed”. We will work with you to ensure reasonable accommodations are made to support your needs.

Want to put your best foot forward on your GiveDirectly application? Take a look at our Candidate Application Prep Guide!

Referrals

Know the right person for this role? Please consider referring them. We offer a reward of $3,000 for a Senior Manager or above role, and $500 for a Manager role, paid if we end up hiring your referral. Thank you for sending great people our way!