Ekow Lewis
@ekowlewis
Senior data scientist specializing in generative AI, NLP, and predictive modeling.
What I'm looking for
I am a senior data scientist with deep experience building production ML systems that deliver business impact across risk, fraud, and customer experience.
At AIG I engineered fraud detection, complaint prediction, and NLP models, led adoption of generative AI in underwriting, and developed RAG systems and LLM-driven classification to improve responsiveness and grounding.
I build end-to-end solutions including data pipelines, model deployment, and executive dashboards, and I mentor teams on best practices for model stability, code quality, and governance.
I collaborate with compliance, legal, and stakeholders to bias-test and audit models, and I seek roles where I can continue to scale responsible AI, improve decision-making, and operationalize advanced analytics.
Experience
Work history, roles, and key accomplishments
Engineered fraud detection, complaint prediction, and NLP models and led adoption of generative AI in underwriting, implementing RAG and LLM systems to improve classification, document summarization, and decisioning that streamlined workflows and improved responsiveness.
Data Scientist
CUNA Mutual Group
May 2017 - May 2019 (2 years)
Developed and operationalized predictive models for sales, churn, and advisor lifetime value, built segmentation and uplift modelling frameworks, and automated data pipelines to improve forecasting, retention, and marketing efficiency.
Education
Degrees, certifications, and relevant coursework
University of Tennessee, Knoxville
Master's degree, Business Analytics
Completed a Master's degree in Business Analytics focusing on data-driven decision making and advanced analytical methods.
University of Saskatchewan
Bachelor of Science in Engineering, Engineering
Completed a Bachelor of Science in Engineering with foundational training in engineering principles and quantitative problem solving.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Salary expectations
Job categories
Skills
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