Job Title: Data Analyst
Location: Remote (Nigeria or South Africa)
Report to: Co-founder
Role Overview
- This is a technical, hands-on role working at the intersection of field data collection, automated data cleaning, and impact measurement. You will own the data systems that underpin our monitoring and evaluation (M&E) framework – from raw SurveyCTO submissions through to clean datasets, dashboards, and the analytical outputs used in donor reporting and programme decision-making.
- The role suits a technically strong analyst comfortable in Python or R, rigorous about data quality in low-resource field settings, and confident working independently on a small, high-performing team.
- Importantly, SafeStart is a newly founded nonprofit that operates nimbly – we seek candidates who are resourceful, entrepreneurial, and comfortable building systems and processes from the ground up.
- We are not an organisation that wants you to pretend you can do it all. We are flexible in the skills the candidate can bring, and we are comfortable to outsource some skills if required.
- If you are excellent at statistical analysis but not too comfortable editing our Supabase backend, we can craft the role in this way. Note too that some of what follows is data-engineering work that is largely built already and fairly stable, once the pipeline is running it needs maintenance rather than constant building, so do not be put off by the technical infrastructure items if your strength is analysis and M&E.
Responsibilities
Data Pipeline & Infrastructure:
- Maintain and extend the raw/clean data architecture in Supabase (PostgreSQL), ensuring SurveyCTO submissions flow correctly through to raw and clean tables.
- Own the automated data-cleaning layer (a Python cleaner orchestrated through n8n) that validates and transforms raw submissions into clean tables, deploying updates through the existing version-controlled workflow.
- Keep SurveyCTO reference datasets (communities, agents, staff) in sync with source files as the programme scales.
- Design and maintain SurveyCTO XLSForms for all M&E data collection instruments, ensuring reliability under poor rural connectivity conditions.
- Build automations (in n8n) to trigger WhatsApp / email / Microsoft Teams alerts based on set programme factors.
M&E System Build & Maintenance:
- Manage parallel monitoring tracks for new and existing communities as defined in the M&E plan, including process-check-only visits at the specified interim rounds.
- Contribute to M&E calculations and study design where required. Where skills align, run ANCOVA-based analyses for programme evaluation.
- Manage the change-request queue: field staff submit requested updates to registered details (agents, leaders, communities); review, approve, and apply the approved changes to the reference datasets.
- Maintain the verification sampling logic that selects field visits for audit (audio audits, revisit calls, co-visits) at the agreed rates, and track the resulting audit tasks to completion.
- Design data entry and validation workflows that account for enumerators using paper-based forms, coordinating manual entry into digital systems accurately and on schedule.
Data Quality & Analysis:
- Monitor incoming field submissions for completeness, plausibility, and consistency; flag anomalies to the Fieldwork Manager for follow-up.
- Produce clean datasets and summary outputs for each M&E survey round.
- Proactively interrogate data beyond routine reporting – surface patterns, anomalies, or emerging trends that have programme implications, even when not asked.
- Maintain a changelog for all dataset versions and cleaning rule updates, ensuring reproducibility.
Reporting & Communication:
- Develop and maintain Power BI dashboards and visualisations presenting programme metrics to leadership, implementation partners, and donors.
- Configure alerts (via n8n to WhatsApp / email / Microsoft Teams) for field staff to surface data-submission issues in near real-time.
- Contribute data sections of donor reports, programme evaluations, and strategic planning documents.
Qualifications
Person Attributes:
- A problem-solver – finds a way through rather than waiting to be told how.
- Communicates clearly in writing and in conversation, including with non-technical colleagues.
- Flexible and open to receiving (and giving) feedback; comfortable working in a fast-moving environment.
- Curious and committed to doing good through evidence-based interventions.
Technical Requirements:
- Bachelor’s degree or higher in statistics, data science, economics, epidemiology, computer science, or a related quantitative field.
- Proficiency in Python or R (or both), including data manipulation and scripting for automated pipelines.
- Experience with relational data models and at least one database or data storage platform.
- Strong Excel skills, including complex formulas, named ranges, and multi-sheet workbook design.
- Ability to write clearly and translate analytical findings for non-technical audiences.
- High attention to detail and a systematic approach to data quality.
Desirable:
- Experience with SurveyCTO, ODK, KoboCollect, or comparable mobile data collection platforms.
- Familiarity with Supabase or PostgreSQL, workflow-automation tools such as n8n, and Power BI (or the ability and inclination to learn them quickly).
- Experience with CI/CD workflows (GitHub Actions or equivalent).
- Background in WASH, public health, international development, or impact evaluation.
- Knowledge of relevant statistical methods and tests (e.g. ANCOVA, non-inferiority analysis, power calculations).
Application Closing Date
7th November, 2026.
How to Apply
Interested and qualified candidates should apply below USING APPLY ONLINE NOW BUTTON
Note
- Applications will be considered on a rolling basis.
- Shortlisted candidates will be invited to an interview and a more detailed assessment.
- SafeStart reserves the right not to appoint.