Job Opportunity: Spatial Data Scientist

News

Job Opportunity: Spatial Data Scientist

October 4, 2025

Please kindly read the entire job posting. Application instructions are located at the end.

Data-Pop Alliance is looking for a Spatial Data Scientist. We are an international nonprofit created in 2013 out of the Harvard Humanitarian Initiative (HHI), the MIT Media Lab and ODI. We bring together researchers, experts, practitioners, and activists to change the world with data through three pillars of work: diagnosing local realities and human problems with data and AI; mobilizing capacities, communities, and ideas towards more data-literate societies; and transforming the systems and processes that underpin our societies and countries.

DPA has partnered with and received funding from organizations such as the Inter-American Development Bank, UNDP, FAO, UN ESCWA, GIZ (German development agency), the Vodafone Institute, Oxfam México and other key international stakeholders to develop projects in Sub-Saharan Africa (SSA), Latin America and the Caribbean (LAC), the Middle-East and North Africa (MENA), and Asia. To learn more about DPA, please consult our website and our “Overview and Outlook 2022-2024” report.

DPA’s projects are managed and carried out by a core team of about 30 people, including Directors, Managers, Officers, Data Scientists, Research Assistants, and Interns.

Dates: Immediate start, full-time position.

Location: Remote; ideally within GMT -1 to +3 for compatibility with the team.

Scope of Work

The Spatial Data Scientist will report to the Data, Technology and Innovation Director and the Technical Manager and collaborate with the tech team. Responsibilities include:

Data Collection and Management

1. - Data Acquisition: Gather spatial data from diverse sources such as satellite imagery, GPS data, remote sensing technologies, and public databases.
  - Data Cleaning and Preprocessing: Clean and preprocess spatial data to ensure accuracy, consistency, and usability. This includes handling missing data, correcting errors, and standardizing formats.
  - Data Storage and Management: Design and manage spatial databases and data warehouses, ensuring efficient storage, retrieval, and management of large volumes of spatial data.

Spatial Analysis and Modeling

1. - Geospatial Analysis: Perform geospatial analyses such as buffer analysis, overlay analysis, and spatial statistics to extract meaningful patterns and trends from spatial data.
  - Predictive Modeling: Develop and implement predictive models using spatial data to forecast trends and outcomes. This may include land use change modeling, environmental impact assessments, and urban growth modeling.
  - Machine Learning: Apply machine learning algorithms to spatial data for tasks such as image classification, object detection, and spatial clustering.

Data Visualization and Reporting

1. - Visualization: Create detailed maps, charts, and interactive visualizations using GIS (Geographic Information Systems) and other data visualization tools to effectively communicate spatial data insights to stakeholders.
  - Reporting: Prepare comprehensive reports and presentations summarizing the results of spatial analyses and providing actionable insights and recommendations.
  - Dashboard Development: Develop interactive dashboards for real-time monitoring and reporting of spatial data and analyses.

Application Development

1. - GIS Application Development: Develop custom GIS applications and tools to facilitate spatial data analysis and visualization for specific projects or organizational needs.
  - Integration with Other Systems: Integrate spatial data and GIS applications with other organizational systems and databases to enhance data accessibility and utility.

Research and Development

1. - Innovation in Methods: Conduct research to develop new methods and techniques for spatial data analysis and modeling.
  - Technology Assessment: Evaluate and adopt new tools and technologies in the field of spatial data science to enhance analytical capabilities.

Collaboration and Support

1. - Cross-functional Collaboration: Work closely with cross-functional teams, including program managers, data scientists, engineers, and policy makers, to understand their spatial data needs and provide tailored solutions.
  - Technical Support and Training: Provide technical support and training to team members and stakeholders on the use of spatial data tools and methodologies.

Fundraising:

- Participate in developing technical grant proposals

Profile/Qualifications

Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related fields.
Some experience around geospatial platform development.
Experience on GIS Application Development.
Experience (not mandatory) on GEE application development.
Knowledge on PowerBI.
Knowledge of version control systems (e.g., Git).
Familiarity with browser testing and debugging
Knowledge of SEO principles
Excellent interpersonal and communication skills.
Strong problem-solving abilities and attention to detail.
Ability to work independently and as part of a diverse, multicultural team.
Bilingual proficiency in English is requisite (able to write and deliver conferences, reports, etc in both languages). French, Arabic or Spanish are highly desirable.
A self-starter, disciplined, driven, eager to learn, grow, and make an impact.
Experience (not mandatory) with Google Earth Engine (GEE) for geospatial and satellite data processing.
Proficiency with geospatial libraries and frameworks such as GeoPandas, Rasterio, Shapely, xarray, rioxarray, GDAL/OGR, Leaflet, Mapbox GL, or OpenLayers.
Experience working with different types of geospatial data (vector, raster, satellite, mobile, social media, administrative, census) and integrating multiple data sources.
Strong analytical skills, including statistical/econometric modeling and machine learning (e.g., regression, classification, clustering, small-area estimation, spatial/temporal modeling) using frameworks like scikit-learn, statsmodels.
Experience building interactive dashboards and analytical products using Power BI, Tableau, or web frameworks (Plotly/Dash, Streamlit, Bokeh, D3.js), with a focus on spatial data visualization.
Familiarity with basic DevOps practices (e.g., testing, CI/CD, Docker is a plus) and documentation for reproducibility.

Candidates should be able to work independently, manage their time wisely, and meet deadlines. They should be detail-focused, reliable, professional, and possess strong research, writing, editing, and analysis skills, as well as excellent communication, and interpersonal skills.

Remuneration

USD $2,000 / month

Recruitment Process

Qualified candidates are requested to submit 1) a CV, and 2) a Cover letter including contact details for two academic or professional references to jobs@datapopalliance.org with the subject line “R2025002-Spatial Data Scientist” by October 15, 6:00 pm EST. Candidates will be reviewed on a rolling basis, so early application is strongly encouraged.

Please note that only complete applications submitted in English will be considered. Due to the large volume of applications, only short-listed candidates will be contacted. Also, rename each document you’ll submit with your name, the position and the type of document you are submitting. Ie. FIRSTNAME LASTNAME_Position_CV and send them in PDF format.

Equal Opportunity

Data-Pop Alliance employs personnel without regard to race, ancestry, place of origin, color, ethnic origin, language, citizenship, creed, religion, gender, sexual orientation, gender identity, age, marital status, physical and/or mental handicap or financial ability. While remaining alert and sensitive to the issue of fair and equitable treatment for all, Data-Pop Alliance has a special concern with the participation and advancement of members of four designated groups that have traditionally been disadvantaged in employment: women, visible minorities, aboriginal peoples and persons with disabilities.