
African Neonatal Outcomes Dashboard
Cut reporting lag by roughly 40% across hospitals with filterable M&E metrics.
I work at the intersection of data analytics, governance, and responsible AI — helping organizations turn complex information into decisions that are accurate, ethical, and impactful. With certification as a CDMP professional and training in AI governance and strategy, I bring both governance discipline and technical depth to the solutions I design. My focus is on building data systems that foster trust: reliable pipelines, clear governance frameworks, and practical AI tools designed with responsibility in mind. For me, good data work is not just about efficiency — it’s about ensuring information serves people, not the other way around.
Implemented validation and lineage patterns and authored AI/data guardrails used across NGO projects.
Delivered dashboards for 200+ stakeholders with automated refresh and narrative insights.
Built fraud, churn and text classifiers and added human-in-the-loop checks and simple model-risk notes.
Orchestrated ingest, transform and serve for health and finance datasets and scripted data quality checks.
Mapped field coverage and developer distributions and layered analytics for decision support.
Prototyped multi-agent research and reporting workflows with governance dashboards.
Tools, technologies, and credentials that back the work.
2025 – Present
2022 – 2025
2019 –
2024 – Present
Check out some of the projects I have worked on recently.
Cut reporting lag by roughly 40% across hospitals with filterable M&E metrics.
Standardized maturity scoring to drive roadmaps and executive-ready adoption plans.
Prioritized relief signals by classifying messages into actionable categories.
Benchmarked more than 1,500 applicants for salary trends and workload balance.
Built a governance framework with roles, business rules, and lifecycle controls; led workshops and training; delivered a final report with risk assessment, incident procedures, and a training roadmap.
Automated PDF extraction to visualize disbursements over time.
Automated PDF extraction to visualize disbursements over time.
Curated perspectives on data strategy, governance, and responsible AI.
The list is not exhaustive. Feel free to reach out for more.
Design and deploy intelligent agents and automated workflows to streamline business operations, reduce repetitive tasks, and scale decision-making. Solutions range from chatbot assistants to backend data workflows, tailored to client needs.
Evaluate the readiness, risks, and potential impacts of AI systems and ensure alignment with business objectives. Conduct a thorough assessment of the impact of AI systems before deployment. Ensure compliance, ethical alignment, and business value through structured reviews.
Develop and evaluate predictive models that deliver measurable ROI. From demand forecasting and uplift modeling to elasticity-aware pricing and inventory optimization, solutions are built with rigorous evaluation and business constraints in mind.
I build data stacks from source to decision — warehouses, feature stores, and APIs feeding into strategy-driven dashboards with automated refresh and clear insights. The outcome: a robust, cost-tuned system that supports daily operations and long-term decisions.
I help organizations design and implement governance frameworks that make data reliable, compliant, and actionable. This covers operating models and stewardship roles, data quality controls, metadata and lineage management, and alignment with regulatory and business outcomes. The goal is not paperwork but practical, outcome-driven governance that empowers teams to use data with confidence.
I support organizations in building and deploying AI and data systems that comply with global and local regulations while remaining practical for business use. This includes conducting Data Protection Impact Assessments (DPIAs), reviewing model risks and biases, and embedding responsible AI guardrails into product and governance lifecycles. By aligning with frameworks such as GDPR, Kenya’s Data Protection Act, and emerging AI standards, I help ensure that innovation is ethical, transparent, and defensible.
I design and ship decision-grade data products: analytics, ML, and the pipelines and platforms that keep them reliable. My work has reduced reporting errors by ~40%, shortened preparation cycles from weeks to days, and lifted margins by 2–4% in pricing pilots. I bring a differentiator most teams lack: governance and responsible-AI rigor baked into delivery — from data quality controls, evaluation, and clear accountability.
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