Data Scientist

Imagine Worldwide

Imagine Worldwide

Data Science
Africa · Remote
Posted on Jul 12, 2025

About Imagine Worldwide

All children have immense potential, but hundreds of millions don’t have access to the learning they need. Imagine Worldwide’s mission is to empower millions of children across Sub-Saharan Africa with the literacy and numeracy skills they need to reach their full potential. We provide an innovative education technology solution and implementation model to the global literacy/numeracy learning crisis using the onebillion application and various toolkits and systems to support implementation . Nine Randomized Control Trials (RCTs) across multiple countries and settings have shown dramatic learning gains, increased school attendance, and gender parity, all for less than $7 per child per year.

Imagine Worldwide partners with governments, organizations, and communities to provide child-directed, tablet-based learning that is accessible, effective, and affordable. We are a California-based (United States) nonprofit organization operating across seven Sub-Saharan African countries. Learn more on our website.

About the Role

The Data Scientist will play an instrumental role in carrying out Imagine’s mission, to design, test, and scale tablet-based learning solutions that enable children to become literate and numerate. The Data Scientist will join a highly committed and collaborative team that is working together to empower every child, everywhere to achieve their full potential. They will work directly with our data team and other functions across the organisation to derive actionable insight from program-related data across our operating countries. We are particularly interested in candidates with a strong developer or programming background who have recently or are eager to transition their technical skills into the analytics and data science domain.

Over the next six years, Imagine’s goal is to serve more than 10 million children in at least four countries, ultimately achieving three times the typical level of literacy and numeracy outcomes of national education systems in Africa (60% fluency by the age of 10, as opposed to 20%). This all while delivering the program at less than $5 per child per year. Being a data-driven organization is key to achieving this goal. The Data Scientist must embody a full-stack approach, bridging data science, analytics, and foundational data engineering to be able to deliver robust and impactful data solutions. The position offers an international, flexible, learning environment to enhance individual career development and growth.

Key Responsibilities

The Data Scientist will be responsible for deriving and communicating actionable insights from Imagine program data to help us improve educational outcomes for children. Their analyses will drive product and process improvements, and involve close collaboration with various internal teams to ensure data integrity and uncover actionable insights. Their primary internal customers include:

  • Programs: Focusing on verifying data integrity to ensure accuracy and reliability, developing data-driven insights, and assisting with reporting development and interpretation of underlying data that may inform operational decisions.
  • Product Management: Focusing on product analytics, data-driven product roadmap development, and data-related fault resolution.
  • Research: Focusing on data source generation, statistical validation, and analytics support for validating research findings.

Their responsibilities will include, but will not be limited to, the following:

Data Strategy

  • Contribute to the development of the organization’s overall analytics strategy, identifying high‑impact use cases for data science.
  • Act as a subject matter expert on analytical methodologies, advising cross‑functional teams on best practices and data‑driven approaches.
  • Stay current with emerging tools and techniques in machine learning, statistical analysis, and data visualisation.

Mentor and guide other analysts on data science methods and career development.Data Acquisition & Preparation

  • Collaborate with data engineering teams to define and refine data requirements for analysis and modeling.
  • Perform exploratory data analysis, data cleaning, and feature engineering to prepare robust datasets.
  • Ensure data quality through thorough validation, profiling, and documentation of data sources and transformations.

Statistical Analysis & Modeling

  • Conduct advanced statistical analyses to uncover trends, patterns, and correlations.
  • Develop, validate, and deploy predictive and prescriptive models (e.g., regression, classification, clustering, time series forecasting) using Python, R, or other appropriate tools.
  • Design and analyse A/B tests and other experimental frameworks to measure impact and inform product decisions.

Visualisation & Reporting

  • Build intuitive dashboards and interactive reports (e.g., Metabase, Tableau, or similar) to communicate insights and model performance to stakeholders.
  • Translate complex analytical results into clear, actionable recommendations tailored to both technical and non‑technical audiences.
  • Continuously monitor key metrics and model health in production, alerting teams to anomalies or drift.

Requirements

Minimum Qualifications

  • Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.
  • Minimum of 5 years in data science, analytics, or related roles.

Ideal Candidate Profile

Proven experience that includes:

Technical Skills:

  • Proficiency in Python (e.g. pandas, scikit‑learn, statsmodels, Flask/Django for basic API development) or R for data manipulation, analysis, and modeling.
  • Strong SQL skills for querying and aggregating large datasets; familiarity with performance optimisation techniques and schema design principles.
  • Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and deployment considerations for production environments.
  • Familiarity with cloud platforms (e.g. AWS, Azure, GCP) and data warehousing solutions (e.g. Snowflake, ClickHouse, BigQuery) is a plus.
  • Competence in data visualisation libraries (e.g. matplotlib, ggplot2) and BI tools (e.g. Metabase, Tableau, Looker).
  • Understanding of experimental design, A/B testing, and causal inference methods.

Analytical & Problem-Solving Skills:

  • Demonstrated ability to frame ambiguous problems, develop hypotheses, and deliver data‑driven solutions.
  • Proven ability to conduct root cause analysis for data anomalies and inconsistencies, working closely with cross-functional teams to resolve issues.
  • Strong critical thinking and attention to detail, with a commitment to data accuracy and reproducibility.

Leadership & Communication:

  • Proven track record of translating technical analyses into clear business insights and strategic recommendations.
  • Exceptional verbal and written communication skills, with experience presenting to senior leadership.
  • Collaborative mindset and ability to influence cross‑functional teams without direct authority, particularly in areas of data quality, metric definition and product iteration.

Qualities

  • Passion for Imagine’s mission and vision
  • Demonstrated commitment to equity in educational access and outcomes
  • Passion for project management
  • Demonstrated ability to think independently and solve problems
  • Collaborative team player; clear and proactive communicator
  • Flexible, adaptable, and able to work in a fast-paced, changing environment

Compensation & Benefits

Salary is competitive and commensurate with experience.

Location

The role is fully remote. The Data Scientist must be based on the African continent with a preference for the countries that Imagine is already operating in. Regional travel to field sites will be required at least every second month, or up to once a month.

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Imagine Worldwide is proud to be an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.