Position Overview:
Green Street’s Forecasting & Data Science team is a tight knit group of enthusiastic quants, actively seeking individuals who are eager to tackle diverse quantitative challenges. We are looking for candidates who possess a strong coding acumen, thrive in a collaborative environment, and can adeptly apply statistical concepts to solving real world challenges in the commercial real estate (CRE) space.

Job Responsibilities:

• Perform quantitative analysis to develop, enhance and expand Green Street’s capabilities in commercial real estate forecasting, data analytics and other technical projects related to CRE
• Ability to collaborate effectively across multiple departments, including Market Analytics, Product and Technology teams
• Proficiently handle large databases and analyze complex datasets to derive valuable insights and provide actionable recommendations
• Excellent communication and documentation skills, both verbal and written
• Demonstrate an ownership attitude and self-starting approach, thriving in a fast-paced environment

Candidate Profile:

• A master’s or PhD degree in a quantitative science discipline, such as Economics, Statistics, Data Science, Econometrics, Math, or Financial Engineering
• 2+ years of experience with Python and SQL for data analysis and manipulation
• Demonstrated experience in data cleaning, validation, and addressing data quality issues
• Experience developing econometric or predictive models using SAS or Python is a plus
• Prior experience in the CRE or CMBS industry is preferred
• This is a hybrid position, requiring time spent working in the London office

Compensation, Benefits and Work Authorization:
In addition to a basic salary, this position is eligible for a performance bonus and benefits (subject to eligibility requirements). Total compensation is based on several factors including, but not limited to, type of position, location, education level, work experience, and certifications. This information is applicable for all full-time positions.
Green Street will not sponsor or transfer employment work visas for this position. Applicants must be currently authorized to work in the United Kingdom without the need for visa sponsorship now or in the future.

Benefits

• Comprehensive benefits package including company provided medical, dental insurance and cash plan
• Company provided life assurance, critical illness and income protection coverage
• Personal pension plan with matched employer contributions
• Company paid holidays and summer half day Fridays
• Access to employee assistance programme and wellbeing resources
• Tax free cycle scheme and IT equipment
• Season ticket loan
• Company sponsorship to further education
• Flexible work arrangements

Company Overview and EEOC/Diversity:
Green Street is a forward-thinking real assets company at the forefront of transforming the commercial real estate market with cutting-edge predictive analytics, data-driven insights, and actionable intelligence. With over 40 years of expertise, Green Street empowers investors, lenders, banks, and industry stakeholders across the U.S., Canada, Europe and Asia to make optimized investment and strategic decisions. To learn more, please visit www.greenstreet.com.
The success of Green Street is directly attributable to the strength of our people. A diverse and inclusive work environment where top talent can thrive, think freely and offer different perspectives makes our insights even stronger. We’re building a company culture where differences are celebrated and valued.

• Perform quantitative analysis to develop, enhance and expand Green Street’s capabilities in commercial real estate forecasting, data analytics and other technical projects related to CRE
• Ability to collaborate effectively across multiple departments, including Market Analytics, Product and Technology teams
• Proficiently handle large databases and analyze complex datasets to derive valuable insights and provide actionable recommendations
• Excellent communication and documentation skills, both verbal and written
• Demonstrate an ownership attitude and self-starting approach, thriving in a fast-paced environmen