Data Analyst (Remote)

About this role

SafeStart Global Inc is seeking a Data Analyst for a remote role (Nigeria or South Africa). The position involves building and maintaining data systems for monitoring and evaluation, from field data collection to clean datasets and dashboards used for donor reporting and programme decisions. The role requires strong technical skills in Python or R, data quality discipline in low-resource field settings, and the ability to work independently in a small, flexible team. SafeStart is a nonprofit organisation implementing a chlorine access programme in Kano State, Nigeria, with plans to expand and potentially work with government delivery. The candidate should be comfortable shaping systems and processes from the ground up and may have responsibilities that span data engineering and analytical work.

What you would do

• Maintain and extend the data architecture in Supabase (PostgreSQL) for raw and clean data from SurveyCTO submissions.
• Manage the automated data cleaning pipeline (Python cleaner via n8n) and deploy updates through versioned workflows.
• Synchronise reference datasets (communities, agents, staff) as the programme scales.
• Design and maintain SurveyCTO XLSForms for M&E data collection under challenging connectivity conditions.
• Create automations in n8n to trigger alerts via WhatsApp, email, or Teams based on programme factors.
• Oversee parallel monitoring tracks for new and existing communities and support M&E calculations and study design where needed.
• Perform ANCOVA-based analyses where skills align and manage change-requests for dataset updates.
• Maintain verification sampling logic for audits and track audit tasks to completion.
• Design data entry and validation workflows accommodating paper-based forms and manual data entry.
• Develop Power BI dashboards and reports for leadership, partners, and donors.

What they are asking for

• Bachelor's degree or higher in a quantitative field (e.g., statistics, data science, economics, epidemiology, computer science).
• Proficiency in Python or R (or both) for data manipulation and automated pipelines.
• Experience with relational data models and at least one database or data storage platform.
• Strong Excel skills with complex formulas and multi-sheet workbooks.
• Ability to communicate analytical findings clearly to non-technical audiences.
• Attention to detail and a systematic approach to data quality.
• Desirable: experience with SurveyCTO, ODK, KoboCollect, Supabase/PostgreSQL, n8n, and Power BI; familiarity with CI/CD workflows; background in WASH or public health; knowledge of methods like ANCOVA and power calculations.

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