Curriculum vitae

Babaniyi
Olaniyi

Senior data scientist and economist with 8+ years building machine-learning and decision-support systems across healthcare, public policy, pricing, and digital products.

9M+insured people represented
100M+healthcare claims processed
€11M+annual pricing leakage protected
13%gross-profit improvement supported

Experience

01

Healthcare AI · Barcelona

Data Scientist

Causal Foundry

Nov 2024—Present
  • Built claims-driven healthcare-financing models used in policy decision-making, supporting modeled liquidity for health centres serving 9M insured people.
  • Designed provider-performance, utilization, patient-outcome, and health-financing decision workflows across more than 100M claims.
  • Reconciled 5,000+ drug SKUs across seven agencies using text similarity and embedding-based matching.
  • Developed anomaly detection and automated indicators that improved oversight across 1,000+ providers.

Pricing · Barcelona

Senior Data Scientist

ZF Group

Feb 2023—Sep 2024
  • Designed pricing-arbitrage and anomaly-detection systems that identified inconsistencies and protected approximately €11M annually.
  • Built elasticity and uplift models across a €500M+ portfolio, contributing to a 13% gross-profit improvement.
  • Productionised PySpark and Databricks pipelines with engineering partners for commercial decision workflows.

Digital health · Barcelona

Data Scientist

Benshi AI

Jul 2021—Feb 2023
  • Forecast pharmacy demand using time-series and deep-learning methods, helping reduce stockouts by 18%.
  • Improved mobile-health engagement with survival models, churn prediction, return models, and behavioural experiments.
  • Designed adaptive interventions and recommendations using contextual bandits and reinforcement-learning concepts.
  • Mentored data scientists and translated technical results for product, research, and policy stakeholders.

Business intelligence · Barcelona

Data & Business Intelligence Analyst

The Alchemist Atelier

2019—2021
  • Built segmentation and churn models to improve communication, retention, and customer satisfaction.
  • Combined multiple data sources into revenue, budget, expense, and KPI dashboards that reduced manual reporting.
  • Analysed acquisition, customer journeys, pricing scenarios, and commercial performance for management decisions.

Political economy · Barcelona

Research Assistant

IAE-CSIC

2019
  • Built newspaper-text collection and predictive-modeling workflows to study political violence and conflict risk.

Research

02

Selected work

See how this experience translates into policy and product outcomes.