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Samuel Miingi

@samuelmiingi

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Financial economist and AI researcher with 15+ years of experience.

United States

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What I'm looking for

I seek a role that allows me to innovate at the intersection of finance and AI, fostering responsible data-driven practices.

I am a financial economist and AI researcher with over 15 years of experience at top-tier institutions. My expertise lies in leveraging machine learning for capital markets, risk analytics, and investment decision-making. I am passionate about education and committed to integrating industry-grade AI methods into finance curricula, guiding future practitioners toward responsible, data-driven innovation.

Throughout my career, I have held significant roles, including Senior Vice President of Quantitative Strategy at J.P. Morgan Private Bank, where I led the integration of machine-learning models into high-net-worth portfolios, boosting forecast accuracy by 37%. My work at Eli Lilly & Company as Director of Financial Engineering resulted in the implementation of predictive models that optimized treasury and FX exposure, saving the company $45 million over five years. I have also contributed to academia as a guest lecturer and mentor, focusing on AI applications in finance.

Experience

Work history, roles, and key accomplishments

Current

Senior Vice President, Quantitative Strategy

Current

J.P. Morgan Private Bank

Jan 2018 - Present (8 years 5 months)

Led integration of machine-learning models into HNW portfolios, boosting forecast accuracy by 37%. Partnered with AI ethics teams to establish model-interpretability standards adopted bank-wide.

Machine Learning Model Interpretability Python R TensorFlow PyTorch

Director of Financial Engineering

Eli Lilly & Company

Jan 2012 - Jan 2017 (5 years)

Implemented predictive models optimizing treasury & FX exposure, saving $45M over 5 years. Co-developed graduate-intern curriculum on ML for pharmaceutical finance.

Financial Engineering Treasury Management Machine Learning Python R SQL

Quantitative Analyst

Cummins Inc.

Jan 2008 - Jan 2012 (4 years)

Built econometric and time-series models forecasting commodity prices. Piloted in-house AI training modules for junior analysts.

Quantitative Analysis Econometrics Time Series Analysis Commodity Forecasting AI Training Python R SQL

Education

Degrees, certifications, and relevant coursework

Indiana University Bloomington

Ph.D., Financial Economics

Grade: Summa Cum Laude

Activities and societies: Awarded the Chancellor's Medal for Academic Excellence.

Focused research on the intersection of financial economics and artificial intelligence. Completed a dissertation titled 'Machine Learning in Capital Markets: Predictive Modeling in Asset Valuation', exploring advanced AI techniques for asset valuation.

Purdue University

Bachelor of Science, Finance & Applied Mathematics

Grade: GPA 3.95/4.0

Activities and societies: Minor in Computer Science; Honors College.

Pursued a rigorous curriculum combining finance and applied mathematics, with a minor in computer science. Participated in the Honors College program, undertaking advanced coursework and research opportunities.