Leaders in Pharmaceutical Business Intelligence (LPBI) Group

Finance Internship: Financial Modeling

Employer Partner: Leaders in Pharmaceutical Business Intelligence (LPBI)

Career(s)

Finance, Statistics, Econometrics, Operations Research, Accounting, Financial Engineering, Quants, Data Science

Overview

LPBI Internships offer the following:

• Affiliation with and mentorship by esteemed scientists and research graduate students.
• References/letter of recommendation
• Description of accomplishments and goals achieved during the internship
• Opportunity to contribute to publications
• Opportunity to collaborate with professionals from various fields

Internship Description

PROJECT: Develop a valuation model for an intellectual property portfolio of digital assets that includes intangible assets as well.

A perspective on the valuation of companies with significant Intangible assets, like LPBI, is presented and analyzed in the following curation on the intangible asset of a firm’s reputation. In the case of LPBI, the intangible assets it possesses are key determinants of its reputation and digital reputation on the internet as is the case in the media world.

Article: The Digital Age Gave Rise to New Definitions – New Benchmarks were born on the World Wide Web for the Intangible Asset of Firm’s Reputation: Pay a Premium for buying e-Reputation

Types of Students Desired/Requirements

College students: Third year/Senior year college or MBA candidates in need of a project to submit (such as a capstone or thesis)

Prerequisites: (Minimum 2)

• Courses in Statistics, Economics, Accounting, Finance, Operations Research, Probability
• Advanced Excel skills (formulas)
• Programming experience – Java or Python
• Advanced research and analytical skills

Structure/Schedule

• Individual (not cohort)
• 12 weeks minimum (mini-project)
• 1 academic year (equivalent to master thesis)
• Two meetings weekly with LPBI until model is finalized
• 12 weeks minimum – flexible schedule
• Zoom 1 time per month with LPBI team

Skills Used/Gained

• Experience with large data
• Economic Modeling
• Financial Modeling
• Optimization Modeling
• Probability Modeling