Omilani Charles
@omilanicharles
Senior data engineer and AI/ML specialist building reliable production analytics.
What I'm looking for
I am a senior data engineer and AI/ML specialist with 10+ years of experience building production-grade data platforms across healthcare, fintech, and real estate domains. I focus on end-to-end ownership—designing pipelines, deploying models, and delivering reliable analytics for high-stakes workflows.
My work has included cutting batch jobs from 45 minutes to seconds with Spark and dbt, embedding GPT-3 and BERT models into live workflows for clinical classification and document analysis, and building real-time fraud detection systems that proactively flag risk.
Technically, I operate across hybrid cloud environments (AWS, Azure, GCP), build feature stores and observability layers, and deploy models with SageMaker, Azure ML, or containerized infrastructure. I prioritize data quality, schema resilience, and automated monitoring to keep APIs quiet and dashboards truthful.
I thrive on complex architectures and tight timelines, delivering event-driven ingestion, real-time scoring, compliance-ready governance, and scalable ML pipelines that integrate into product workflows and operational decision-making.
Experience
Work history, roles, and key accomplishments
Senior Data Engineer
Qualia
Sep 2022 - Jun 2025 (2 years 9 months)
Led design and delivery of real-time fraud detection, GPT-based document classification, and a Delta Lakehouse for title data, reducing processing latency to milliseconds and automating document routing to cut manual review time. Built feature stores, monitoring, and compliant governance enabling scalable production ML and regulatory reporting.
Data Scientist
UnitedHealth Group
May 2019 - Jul 2022 (3 years 2 months)
Built clinical data integration and risk analytics for COVID-19 surge forecasting and developed claims fraud detection engines, enabling near-real-time decisioning and automated anomaly detection to prevent overpayments. Delivered NLP pipelines and models that improved clinical signal extraction from unstructured notes.
Engineered low-latency transaction ETL and lakehouse infrastructure powering merchant analytics, experimentation, and credit risk scoring, streaming millions of daily transactions and enabling real-time merchant dashboards and loan risk decisions.
Education
Degrees, certifications, and relevant coursework
Stanford University
Master of Science, Computer Science
Completed a Master’s degree in Computer Science at Stanford University, focusing on advanced machine learning and systems for data engineering.
Stanford University
Bachelor of Science, Computer Science
Completed a Bachelor’s degree in Computer Science at Stanford University with coursework in algorithms, systems, and machine learning.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
Skills
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