2022 Investment Management Summer Analyst Program - Real Estate Investing (San Francisco)
- The Investment Management Summer Analyst Program is a 10-week program consisting of one week of training and nine weeks working within a specific IM team.
- Across all IM teams, the curriculum is designed to equip Summer Analysts with the fundamental skills they need to be successful in IM.
- During the 10-week program, Summer Analysts experience the culture and atmosphere of Morgan Stanley by performing a role similar to a Full-Time Analyst.
- IM's Real Estate Investing (REI) team offers the opportunity to learn from a leading global real estate investment platform that manages opportunistic and core investment strategies.
- Opportunities with the REI team are in New York and San Francisco; this specific application is for San Francisco.
- Help execute business development initiatives
- Work on several deal teams and gain exposure to senior-level financial and strategic decision-makers at some of the world's largest real estate companies
- Conduct market and financial due diligence on various real estate opportunities
- Participate in transactions from the principal or private equity perspective on behalf of proprietary real estate investment funds, including North Haven opportunistic funds and the Prime Property Fund
- Conduct investment underwriting, transaction execution, and create presentations regarding investment opportunities
- Pursuing a Bachelor's degree and will graduate between December 2022 and June 2023
- Outstanding analytical and quantitative skills
- Excellent communication skills, both verbal and written
- Strong team player; ability to collaborate with colleagues across REI and the broader organization
- Self-starter with the ability to work independently
- Driven, highly motivated and results-focused
- Strong organizational skills with the ability to manage time efficiently and effectively
- Detail oriented and have the ability to work efficiently within tight time constraint
- Proficiency in Excel, and experience with Argus modeling and presentations preferred