Job Title: Data Scientist
Date Posted: 07/07/2026
Job Type: Full Time
Employer: Educate!
Industry: IT
Salary: Open
Location: Nairobi
Country: Kenya
Deadline: 21/07/2026
Looking for an IT job in Kenya? Educate! is hiring a Data Scientist skilled in tech systems like SQL/BigQuery, data visualization (Looker/Tableau), Git, and advanced data analytics.
Job Overview
You
will have the mandate to build and codify the Data Science function from the
ground up. Working directly with Global Directors across Product, Tech, and
Evaluation, you will bridge the gap between complex model outputs and
actionable policy. Whether you are designing sophisticated machine learning
frameworks or translating high-signal narratives for partners, your work will
be the an engine for evidence-based decision-making. If you are a pragmatic
technologist who is driven by the desire to see your code manifest as
real-world impact, this is your next career-defining challenge.
Responsibilities
Theory-Driven
Causal Discovery
- Construct Causal Frameworks: Move beyond correlation. You will
leverage behavioral science and economic theory to develop “Theories of
Change” that map the latent social mechanisms driving youth success.
- Hypothesis-Led Feature Engineering: Don’t just throw data at a wall.
You’ll formulate and test rigorous hypotheses to identify the “why” behind
program performance, turning social science theory into predictive
variables.
- Inform Product Strategy: Act as a strategic partner to Product and
Evaluation teams, identifying high-leverage use cases where data-driven
insights can fundamentally pivot program design or delivery.
Advanced Analytics and
Pragmatic Modeling
- Build Outcome-Focused Models: Develop and maintain sophisticated
models—from rule-based frameworks to advanced ML—designed to predict and
drive key indicators like student retention, livelihood gains, and
pedagogy adoption.
- Analyze Heterogeneity: Go deeper than “average” results. You will
employ advanced statistical tactics to examine how program impacts vary
across different demographics and contexts.
- Prioritize Impact over Complexity: Lead with a “Minimum Viable
Model” mindset, selecting the right tool for the job to ensure technical
solutions are maintainable, scalable, and—most importantly—useful for
field operations.
Strategic
Translation & Insight “Last-Mile”
- Data Storytelling & Visualization: Synthesize complex
statistical findings into compelling, high-signal narratives and visuals
that empower non-technical leaders and government partners to make
evidence-based decisions.
- Close the Insight-Action Loop: Co-create with Product and Eval teams
to ensure model outputs aren’t just “reports” but are deployed as A/B
tests, product experiments, or model updates.
- Decision-Support Standardization: Establish a unified framework for
data storytelling, ensuring that every analysis cycle culminates in a
clear “Go/No-Go” decision for stakeholders.
Building the Data
Science Function
- Design the Data Science Lifecycle at Educate!: Own the end-to-end
Data Science workflow at Educate!—from initial intake and prioritization
to validation and productionalization.
- Build the Organizational Memory: Implement a “Lessons Learned”
framework that codifies wins and “productive failures,” ensuring the
team’s collective intelligence grows with every model iteration.
- Cross-Functional Infrastructure Strategy: Collaborate with Tech,
Metrics, and RME leads to ensure our data stack and pipelines evolve to
support increasingly sophisticated analytical needs.
Qualifications
- Master’s in a Social Science field (Economics, Sociology,
Psychology, Public Policy) with a heavy quantitative focus, OR a degree in
Data Science/Statistics with significant experience in social research.
- Proficiency in R or Python for
data manipulation and statistical analysis.
- Strong command of SQL for querying complex
databases.
- Experience with causal inference, longitudinal data analysis, and
econometrics.
- Proven track record of designing surveys, handling “messy”
real-world data from emerging markets, and working with impact evaluation
frameworks.
- Ability to explain a “p-value” to a teacher and “youth agency”
to a software engineer.
- A deep passion for education reform, youth empowerment, and the
development landscape in East Africa.
Technical Stack (Preferred)
- Languages: Python (pandas, scikit-learn, statsmodels) or R (tidyverse,
ggplot2, lme4)
- Tools:
- SQL: BigQuerySQL for structured data
- Version Control: Git/GitHub,
- Field Data Collection: ODK/SurveyCTO
- Data Visualization: Looker, Tableau
- Unstructured/Semi-structured Data:
- Familiarity working with semi-structured data (JSON, nested fields,
open text fields)
- Experience integrating qualitative context (program documentation,
transcripts) into quantitative analysis workflows
- Exposure to text analysis methods — thematic coding, basic NLP, or
LLM-based feature extraction
- Methods: RCTs, Propensity Score Matching, Difference-in-Differences,
and basic Machine Learning (Random Forests, Clustering).
- Fits our Five Cultural Tenets (see What is Educate! About? below);
Learn more by looking at Educate!’s culture deck here
How to Apply
