[Remote] Data Analyst, Internal Audit

Note: The job is a remote job and is open to candidates in USA. GiveDirectly is a global organization that delivers cash directly to people living in poverty. The Data Analyst will analyze operational, payments, and enrollment data to identify fraud risks, support investigations, develop risk indicators, and translate findings into actionable recommendations. The role also partners with Product, Data, and Engineering teams to improve fraud-detection tooling, data quality, and analytical practices.

Responsibilities

• Analyze fraud risk trends: Mine enrollment, payment, survey, and field-operations data to identify patterns, anomalies, and emerging fraud typologies (e.g., duplicate enrollments, collusion, identity fraud, diversion of funds) across GD's programs and geographies
• Design and oversee fraud-risk indicators: Build, validate, and maintain recurring monitoring in partnership with central data and operational control owners
• Identify data quality issues in data currently collected by Internal Audit, and help design and implement process improvements to resolve them
• Embed data-driven thinking into IA design: Identify fraud-related decisions where GiveDirectly should be more data-driven, and incorporate this into Internal Audit process design
• Translate findings into action: Package analysis into clear, credible briefs and presentations for country teams, operations leadership, and senior management, with concrete recommendations for reducing fraud risk
• Support fraud investigations: Provide data pulls, quantify exposure, and help reconstruct events for specific cases — ensuring analysis is reproducible and audit-ready, with documented queries, data lineage, assumptions, exclusions, and QA checks
• Partner with Product and Central Data on fraud-detection tooling: Translate validated risk signals into product requirements, contribute domain expertise and acceptance criteria, and test whether controls operate as intended — while maintaining clear ownership and independence boundaries
• Partner with Data Engineering on upstream data quality and pipeline improvements, while owning the downstream analytical layer
• Strengthen methodology over time: Back-test risk indicators against investigated cases, monitor precision, coverage, and false-positive rates, and refine based on outcomes and emerging risks
• Communicate uncertainty honestly: Distinguish confirmed fraud from suspicious-but-unconfirmed patterns, helping stakeholders make decisions without overstating findings

Skills

• Location: Remote, with a requirement to overlap with an East Africa timezone by at least 3 hours.
• We can only employ people in certain places at the moment, so it's worth checking our [current list of eligible countries](https://perfectwiki.page/p/iOeyfUha_9) to see if yours is included
• We are unable to sponsor or take over sponsorship of employment visas in the U.S. or U.K. at this time.
• 4+ years of experience in data analysis, audit, risk, or a related analytical role; experience in internal audit, fraud/forensics, or a nonprofit/development context is a plus but not required
• Strong SQL skills and comfort working directly in large, sometimes messy operational datasets (Salesforce data, payments data, survey data)
• Experience using Python for reproducible analysis, automation, record linkage, anomaly investigation, or data-quality testing is strongly preferred
• Familiarity with analytical notebooks, version control, and documenting analysis so it can be reviewed and reproduced by others is a plus
• Experience with visualization tools (e.g., Looker, Tableau, Power BI) and/or Python/R for analysis
• Demonstrated ability to turn ambiguous, exploratory analysis into a clear, defensible narrative for non-technical stakeholders
• Experience or strong interest in working cross-functionally with product and engineering teams to translate analytical needs into product requirements
• Sound judgment on evidence quality: knowing the difference between a real signal and noise, and communicating that distinction transparently
• High integrity and discretion — this role will have visibility into sensitive information about staff, recipients, and active investigations
• Alignment with GiveDirectly's values, including prioritizing recipient wellbeing above all else
• Experience using Python for reproducible analysis, automation, record linkage, anomaly investigation, or data-quality testing is strongly preferred

Benefits

• The benefits stipend may be used to cover benefits or taken as additional taxable income.
• Annual Benefits Stipend: $21,393 for United States employees.
• Annual Benefits Stipend: £2,760 for United Kingdom employees.
• Annual Benefits Stipend: $0 for Kenya employees.
• A robust health benefits plan (exact details will vary by country)
• Flexible paid time off that staff is encouraged to take
• Allowances for desk set-up and learning and development
• A supportive team that works hard and cares hard
• A reward of $3,000 for a Senior Manager or above role, and $500 for a Manager role, paid if we end up hiring your referral.

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