Open to data analytics, healthcare analytics, BI, and responsible AI opportunities

Oluwatoyin Olawale Akadiri

Data Analyst Big Data Analytics & AI Researcher

I build data-driven solutions that help organizations make better decisions through Business Intelligence, Healthcare Analytics, Machine Learning, and Responsible AI.

Verified certificationMicrosoft Certified: Power BI Data Analyst AssociateIssued by Microsoft · Oct 2026 · Exam PL-300
Verify

Professional highlights

Applied analytics experience with a research foundation.

Current focus, timeline, and the roles I fit best.

Currently

Current focus

  • Graduate
    M.S. in Big Data AnalyticsGraduate study focused on data systems, machine learning, and applied analytics.
  • BI
    Healthcare dashboardsBuilding Tableau and reporting workflows that support lead intelligence and stakeholder decisions.
  • AI
    Trustworthy AI researchResearching privacy-preserving, explainable, and responsible AI for high-impact data environments.
  • Open
    Data analytics opportunitiesOpen to Data Analyst, BI Analyst, Healthcare Analytics, and responsible AI research roles.

Timeline

Professional timeline

  1. Bachelor’s DegreeAnalytical, policy, and research foundation.
  2. Master of Business AdministrationBusiness strategy, operations, and management training.
  3. MedicidiomData analytics and business intelligence internship experience.
  4. M.S. Big Data AnalyticsGraduate study, expected completion.
  5. Microsoft Certified: Power BI Data Analyst AssociateVerified Microsoft credential (PL-300).

Role fit

Where I create value

I connect stakeholder questions to clean data pipelines, visual dashboards, transparent analysis, and responsible AI thinking.

Data AnalystBusiness Intelligence AnalystReporting & KPI AnalystHealthcare Data AnalystMachine Learning Analyst
SQLPythonTableauPower BIMachine LearningResponsible AI

Research snapshot

Research interests

My research interests focus on trustworthy, privacy-preserving, and generalizable AI systems for healthcare and other high-impact data environments.

01

Trustworthy AI

Explainability, fairness, privacy, and reliable AI evaluation for high-stakes decision support.

02

Federated & privacy-preserving learning

Model collaboration without unnecessary centralization of sensitive data.

03

Healthcare data systems

Analytics workflows that connect clinical, operational, and multimodal data signals responsibly.

Featured Publication

Featured publication

The full list is on the Publications page.

2025Peer reviewed

Collaborative Intelligence Databases (CID): Harnessing AI for Privacy-Preserving Multi-Source Data Management

Journal: Global Journal of Engineering and Technology Advances, 24(3), 406–416.

Research on privacy-preserving, multi-source data collaboration using AI-based access control, federated learning, differential privacy, and related techniques.

Let’s work together

Let’s talk

Open to Data Analyst, BI, and healthcare analytics roles, and to research collaboration.