Senior Data Scientist, MNO Data
New
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GiveDirectlyMobile network data
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.Full-TimeManager
SalaryUnited 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.
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Job Details
- Languages
- English (required); French, Portuguese, Swahili or Spanish (preferred).
- Required Skills
- PythonSQLMachine Learning
Requirements
- Strong mathematical modeling, machine learning, and statistics skills.
- Deep comfort with spatio-temporal data, including temporal filtering, GIS, probability distributions, combinatorial reasoning, and sparse, irregular observations.
- Ability to reason without ground truth and defend parameter choices based on the shape of the data.
- Ability to balance analytical accuracy with operational implementability and explain the trade-offs.
- Excellent communication and relationship-building skills, including explaining methods and limitations to technical and non-technical audiences.
- Experience writing technical specifications that other teams can implement correctly.
- Ability to read and review SQL and Python written by others.
- Understanding of large data volumes and databases sufficient to judge when analytical simplification is required.
- Commitment to privacy by design and confidentiality, including experience handling commercially sensitive partner data.
- Experience designing training materials that changed how non-specialist colleagues used a data source.
- Comfort working in fast-moving contexts where the brief or stakeholder understanding may shift.
- Comfort with substantial international travel, including to fragile and post-disaster contexts.
Responsibilities
- Improve and extend analytical method templates for inferring where people live from MNO data, and for detecting displacement or estimating poverty where needed.
- Design new methods when an intervention requires them.
- Support technical conversations with operators by clarifying needed data and steering discussions toward workable technical designs.
- Assess what can be inferred from each operator’s data, including its types, sparsity, geography, and targeted areas.
- Write tests and specifications, including steps, parameters, pseudocode, and validation criteria, for MNO data engineers to implement.
- Guide operator engineering teams through implementation and adapt methods to data-volume and computational constraints.
- Run in-country workshops and, where feasible, tune parameters using statistical tests and distributions.
- Feed new analytical and implementation elements back into standard templates.
- Design analyses to minimize shared data and use privacy-enhancing technologies where useful; protect operator confidentiality and improve internal data security processes and tools.
- Build training materials to help technical and non-technical colleagues understand the data’s strengths and limitations.
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