Data Scientist

About Educate!

Educate! works to expand youth opportunity across Africa, with a focus on helping young people learn, earn, and thrive. The organization develops scalable employment and livelihood solutions for youth, including an employment-oriented school subject for secondary schools and boot camps for out-of-school youth, especially marginalized rural girls and young women. Its work has reached more than 500,000 young people across Uganda, Rwanda, Kenya, and Tanzania, and it has grown into East Africa’s largest provider of youth employment and skills services.

The team includes more than 300 staff members, most of them African, along with 300 volunteer youth mentors. Educate! emphasizes a strong, growth-oriented culture and has been recognized by global foundations and institutions for its education and systems-change work.

Role Overview

Educate! is hiring a Data Scientist to help shape how evidence informs program design and decision-making. This is a lead-level opportunity for someone who can combine social science thinking with advanced analytics to uncover the mechanisms behind youth success, not just describe outcomes. The role sits at the intersection of theory, product, technology, and evaluation, and will help build the data science function from the ground up.

You will work closely with leaders across Product, Tech, and Evaluation to translate model outputs into practical actions, experiments, and policy choices. The position is suited to a pragmatic problem-solver who wants their analytical work to create measurable real-world impact.

What You Will Do

• Develop causal frameworks that connect behavioral and economic theory to the drivers of youth outcomes.
• Formulate and test hypotheses to identify the factors behind program performance and convert theory into useful features.
• Partner with Product and Evaluation teams to identify high-impact opportunities where data can influence program design or delivery.
• Create and maintain models, ranging from simple rule-based approaches to more advanced machine learning systems, to forecast outcomes such as retention, livelihood gains, and pedagogy adoption.
• Examine how results differ across populations and contexts using statistical methods suited to heterogeneous effects.
• Choose practical, maintainable approaches over unnecessary complexity and use a minimum-viable-model mindset.
• Turn statistical results into clear stories, dashboards, and visuals for non-technical leaders and government stakeholders.
• Work with Product and Evaluation to ensure findings lead to experiments, product adjustments, or model improvements.
• Create a standard approach for decision-support outputs so each analysis cycle ends with a clear go or no-go recommendation.
• Own the full data science workflow, from intake and prioritization through validation and production use.
• Build an organizational learning system that captures successful approaches as well as useful failures.
• Coordinate with Tech, Metrics, and RME leaders to strengthen the data stack and pipelines for future analytical needs.

Requirements

• A master’s degree in a social science discipline such as Economics, Sociology, Psychology, or Public Policy with strong quantitative training, or a Data Science/Statistics degree paired with substantial social research experience.
• Strong programming ability in either R or Python for data manipulation and statistical analysis.
• Solid SQL skills for working with complex datasets.
• Hands-on experience with causal inference, longitudinal analysis, and econometric methods.
• Experience creating surveys, working with messy real-world data, and using impact evaluation frameworks, particularly in emerging market settings.
• Comfort explaining technical findings in simple terms to both education practitioners and technical colleagues.
• Strong commitment to education reform, youth empowerment, and the development sector in East Africa.
• Preferred technical exposure: Python libraries such as pandas, scikit-learn, and statsmodels, or R packages such as tidyverse, ggplot2, and lme4.
• Familiarity with BigQuery SQL, Git/GitHub, ODK or SurveyCTO, and visualization tools such as Looker or Tableau.
• Ability to work with semi-structured and unstructured data, including JSON, nested fields, and open-text responses.
• Experience blending qualitative context such as program documents or transcripts into quantitative analysis.
• Exposure to text analysis methods, thematic coding, basic NLP, or LLM-assisted feature extraction.
• Working knowledge of methods such as randomized controlled trials, propensity score matching, difference-in-differences, random forests, and clustering.
• Fit with Educate!’s five cultural tenets and collaborative, mission-driven way of working.

Additional Information

The role can be based in one of Educate!’s East Africa offices, with Kenya or Uganda preferred.

Applications are reviewed on a rolling basis, and interviews are expected to begin soon.

Candidates are encouraged to apply even if they do not meet every listed requirement, and women and people from all backgrounds are strongly encouraged to apply.

All candidates must complete child and youth safety screening and provide a Certificate of Good Conduct. Employment offers may be withdrawn if any risks to youth are identified.

Culture and Values

Educate! expects team members to contribute beyond their formal role, keep growing, and actively help strengthen the organization’s impact. Its five core values are: putting youth first and staying impact-focused; exceeding expectations; continuously learning; working as one team with many perspectives; and maintaining a startup mindset that embraces change, experimentation, and speed.

Everyone at the organization, from interns to the executive director, is assessed against these values. Educate! also aims to maintain an inclusive environment for people from different cultures, backgrounds, and life experiences.

What We Offer

• A lively, mission-led workplace with a supportive and enjoyable team.
• A salary that will be competitive and aligned with experience.
• Opportunities for learning and professional growth.