Data Analytics for Pricing Analysts in Excel

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Created by: Michael McDonald

Produced in 2018

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Course Description

Discover how to make smarter product pricing decisions that maximize your organization's profits. In this course, instructor Michael McDonald goes over using scenario analysis, price optimization, and variance analysis to model the data analytics behind pricing . Michael explains how to determinebundle pricingin a scenario, estimate price elasticity, compute price optimization profits with one variable or many variables, balance price and sales volume considerations, and more. If you'd like to pursue a career in corporate finance- "particularly as a pricing analyst in an insurance, retail, manufacturing, or technology firm- "then this course can help equip you with the skills you need to help your company succeed in today's economy.

Intermediate Level

Time: 1h 26m

Instructor Details

Michael McDonald

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Michael McDonald is a researcher and professor of finance at Fairfield University.

He has extensive programming skills in SAS, Stata, Python, R, and SQL, among other programming languages. His past work experience includes using these programming languages to analyze big data sets in finance and economics and develop trading strategies based on data mining. He has done extensive work in investment banking, at tech startups, hedge funds, and on a wide variety of consulting projects. He has a track record of authoring creative and practical course materials for a variety of subject areas across business disciplines.

Michael's core knowledge is focused on financial markets and investment decision-making. He has helped advise firms on capital investments, valuation issues, and capital allocation to enhance business strategy. He is the author of multiple research studies addressing complex questions across the finance discipline. Michael's work has been cited by the Wall Street Journal, Bloomberg, the CFA Institute, and many others.