Applied AI and Data Analytics Director - General Duties

Organization Context: US-based nonprofit focused on short-term missions, primarily operating in Latin America.

The Applied AI and Data Analytics Director is responsible for integrating advanced data science, statistical modeling, and machine learning/AI tools to optimize organizational performance, enhance mission safety, and maximize fundraising effectiveness. This role translates organizational questions into data-driven solutions.

I. Data Strategy & Governance

1. Data Infrastructure: Design, implement, and maintain a centralized data warehouse and analytics platform, ensuring secure and standardized data collection across all departments (Operations, Finance, Fundraising, Participant Registration).

2. AI Ethics and Policy: Establish ethical guidelines for the use of AI/ML models, ensuring fairness, transparency, and non-bias, particularly when modeling risks related to specific demographics or mission locations.

3. Data Security & Privacy: Work with Legal Counsel to ensure all collected data, especially international partner and participant data, complies with applicable U.S. and Latin American data privacy regulations.

4. Reporting Automation: Develop and maintain automated dashboards and visualization tools (leveraging predictive and descriptive analytics) to provide Executive Leadership (CEO, CFO, COO) with real-time, actionable insights.

II. Operational Intelligence & Optimization

1. Risk Modeling: Develop predictive models to assess and score mission-related risks (e.g., security risk, political instability, public health threat severity) based on real-time news, travel advisories, and historical incident data.

2. Logistics Optimization: Apply algorithms to optimize short-term mission trip scheduling, resource allocation (equipment, vehicles), and travel routing (flights, in-country travel) to minimize costs and transit time.

3. Language and Communication Tools: Integrate and manage the use of advanced language models and translation APIs to improve the efficiency and accuracy of communications with in-country partners and translation of mission documents.

4. Impact Measurement: Design frameworks and models (e.g., statistical analysis of baseline vs. post-mission metrics) to rigorously measure and quantify the short-term and long-term effectiveness and impact of mission projects.

III. Fundraising & Donor Analytics

1. Predictive Fundraising: Develop machine learning models to forecast donor attrition (churn), predict potential high-value donors, and estimate the optimal timing and segmentation for fundraising appeals.

2. Campaign ROI Analysis: Conduct rigorous analysis on the return on investment (ROI) for various fundraising channels and campaigns, providing data-backed recommendations for future allocation of marketing resources.

3. Stewardship Personalization: Utilize data analytics to identify donor preferences and personalize stewardship communications, increasing donor engagement and loyalty.

IV. Technology Integration & Support

1. Tool Evaluation: Research and evaluate third-party AI and data solutions (e.g., generative AI for content creation, specialized logistics software) for potential integration into the organization's technology stack.

2. Training and Literacy: Lead training initiatives to improve data literacy across all departments, enabling staff to effectively utilize reporting tools and understand data-driven decision-making.

Reporting Structure: Reports to the CFO/Treasurer or the COO/Vice President, depending on the organizational focus (Financial Analytics vs. Operational Efficiency). Core Competencies: Data science, Python/R, statistical modeling (Regression, Classification, Time Series), cloud data platforms (e.g., GCP, AWS), and data visualization.