ABOUT GREYSTAR

Greystar is a leading, fully integrated global real estate company offering expertise in property management, investment management, development, and construction services in institutional-quality rental housing. Headquartered in Charleston, South Carolina, Greystar manages and operates over $300 billion of real estate in nearly 250 markets globally with offices throughout North America, Europe, South America, and the Asia-Pacific region. Greystar is the largest operator of apartments in the United States, manages over 1,000,000 units/beds globally, and has a robust institutional investment management platform comprised of nearly $78 billion of assets under management, including over $35 billion of development assets. Greystar was founded by Bob Faith in 1993 to become a provider of world-class service in the rental residential real estate business. To learn more, visit www.greystar.com.

JOB DESCRIPTION SUMMARY

The Data Scientist will be responsible for analysing large sets of structured and unstructured data to discover patterns, derive actionable insights, and develop data-driven solutions for business challenges. This role combines computer science, statistics, and mathematics skills to interpret and process data, using advanced analytics technologies, including machine learning and predictive modelling. The Data Scientist will work closely with business stakeholders to understand their goals and determine how data can be used to achieve those goals. This role will also include the effective management of our data-lake ensuring that the data available meets our business needs.

JOB DESCRIPTION

Roles & Responsibilities

• Act as technical lead on data projects, aiding their completion by providing insight on best practices and identifying common pitfalls that slow development
• Develop and implement advanced analytics models and machine learning algorithms to analyze large datasets and provide actionable insights.
• Visualize data and findings in a clear and compelling manner, tailored to the audience's level of expertise.
• Build data products that embed data analytics within our internal processes, e.g. internal apps for a range of stakeholders.
• Stay abreast of industry trends and advancements in data science and machine learning to incorporate best practices into our operations.
• Ensure data quality and integrity through rigorous validation and testing of models and algorithms.
• Testing data mining models to select the most appropriate ones for use on a project.
• Collaborating with engineering and product development teams to implement and integrate new analytical solutions into products.
• Working with engineering team to ensure data is readily available in a useable manner within the data-lake.
• Act as a change agent within organisation, identifying and delivering new solutions and models for understanding our data and performance.

Skills & Qualifications

• Advanced degree in Machine-Learning, AI, Computer Science, Statistics, Mathematics, or a related field.
• Strong problem-solving skills with an emphasis on product development.
• Excellent SQL skills to enable effective querying of data and understanding of data architecture
• Experience using statistical computer languages (R/Python) to manipulate data, draw insights from large data sets
• Experience building GPTs or similar LLMs (preferrable).
• Experience with Databricks or similar applications
• Experience with data visualization tools, such as Tableau, Power BI, or similar.
• Experience in using a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Experience with advanced statistical techniques and concepts and experience with applications.
• Experience with using API’s to both retrieve and insert data to and from systems.