Babaniyi Olaniyi

About

Babs Olaniyi builds machine learning systems for healthcare AI, pricing, experimentation, and decision science.

I am a Data Scientist at Causal Foundry. My work combines statistical modeling, machine learning engineering, health analytics, business translation, and experimentation to help teams make better decisions from complex data.

What I Do

Applied machine learning

I design models for healthcare financing, provider performance, pricing, forecasting, churn, recommendations, user engagement, and operational decision support.

Experimentation and causal thinking

I use A/B testing, multi-armed bandits, survival analysis, reinforcement learning, and causal inference to understand behavior and design interventions.

Business translation

I convert ambiguous business questions into measurable data science problems, then communicate tradeoffs clearly to technical and non-technical stakeholders.

Data products

I build analysis pipelines, dashboards, and model workflows using Python, SQL, Spark, BigQuery, Databricks, MLflow, Airflow, and modern ML libraries.

Timeline

Nov 2024 - Present

Data Scientist, Causal Foundry

Healthcare AI, claims analytics, provider-performance models, health financing decision support, anomaly detection, and production monitoring systems across large-scale healthcare data.

Feb 2023 - Sep 2024

Senior Data Scientist, ZF Group

Pricing optimization, elasticity and uplift modeling, anomaly detection, customer pricing corrections, and production ML pipelines for commercial decision-making.

Jul 2021 - Feb 2023

Data Scientist, Benshi AI

Demand forecasting, recommender systems, survival models, and mobile health engagement analytics for users in low- and middle-income markets.

2019 - 2021

Data and Business Intelligence Analyst, The Alchemist Atelier

Customer segmentation, churn modeling, revenue dashboards, acquisition analysis, and business intelligence for retail and e-commerce decisions.

2019

Research Assistant, IAE CSIC

Built data collection and predictive modeling workflows using newspaper text to study political violence and conflict risk.

2017 - 2019

MSc Quantitative Economics

University of Paris 1 Pantheon-Sorbonne and Autonomous University of Barcelona, supported by an Erasmus Mundus scholarship.