Manager, Inclusive Innovation & Analytics

Responsibilities

AI/ML Development

• ·Drive a strategy, use cases, solutions, and partnerships to design, build, implement, and scale AI/ML models that address inclusive growth and social impact challenges.
• Ensure ethical AI practices, including bias detection and mitigation, transparency, and fairness.

Data Engineering/ Backend Data Integration

• Architect and maintain scalable data pipelines and APIs for ingesting, processing, and analyzing structured, unstructured, and curated datasets (e.g., text, audio, open data) in an integrated data management system.
• Implement DevOps practices for model deployment, monitoring, and CI/CD workflows.
• Ensure data quality, integrity, security, privacy regulations, and compliance across cloud environments (GCP, Azure).

Strategic Convenings & Stakeholder Engagement

• Translate technical insights into actionable strategies for stakeholders in philanthropy, government, and civil society.
• Plan and execute convenings, roundtables, and workshops by providing data-driven insights, technical demonstrations, and AI prototypes that inform policy and program design.
• Develop agendas, curate speakers, and facilitate dialogue that drive actionable outcomes.
• Actively participate in technical communities and conversations to monitor emerging data science and AI trends, use cases, and breakthroughs in the field.
• Manage a diverse portfolio of grants while delivering strong outcomes and outputs.
• Advise on and support the Center’s evolving cybersecurity work across its portfolio.

Skillset

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Public Policy, or a related field.
• 5+ years of experience in AI/ML development (preferred), data engineering, or a related technical role.
• Proven experience managing multi-stakeholder initiatives or convenings.
• Strong programming skills in Python and experience with DevOps tools and practices.
• Experience writing policy briefs, strategy documents, and technical memos.
• Proven ability to translate technical findings into accessible language for non-technical stakeholders.
• Ability to define KPIs and track outcomes for convenings and technical initiatives; use of M&E frameworks to assess program effectiveness.
• Experience curating speakers, developing agendas, moderating discussions, managing event logistics, stakeholder coordination, and follow-up strategies.
• Proven ability to manage complex technical projects with cross-functional teams.
• Strong understanding of data processing and backend systems.
• Experience managing grants or program portfolios, including budgeting and reporting.
• Familiarity with philanthropic or nonprofit funding cycles and impact measurement.
• Programming & DevOps: Proficient in data analysis tools (e.g., Python, R, SQL); experience with DevOps practices and tools for scalable deployment (FastAPI, Docker, Streamlit, CI/CD, containerization, model monitoring, infrastructure as code).
• Data Engineering: ETL pipelines, APIs, structured and unstructured data processing
• Data Visualization: Experience with data visualization platforms (e.g., Tableau, Power BI, D3.js)