Company Description

Home Partners of America (HPA) is a residential real estate investment company committed to providing responsible households with a New Path to Homeownership through its innovative Lease with a Right to Purchase Program.

Objective

The Data Scientist will work with production data and systems used in HPA’s most critical business intelligence and data analytics tasks. Projects will center on working with large sets of data around real estate, credit underwriting, consumer behavior and property-level information such as maintenance spend and rental payment tendencies to create forecasts and models. Other projects will include further development of already existing algorithms and models for determining rent pricing strategies, home values, portfolio analysis and management, risk modeling of consumers and other data analytics exercises as required. The Data Scientist can expect to be writing code and scripting on a daily basis, as well as gaining exposure to data management, data storage and data visualization techniques. This position supports the activities of the Information Technology department and will work directly with the company’s key decision makers and senior management team on a regular basis.

Responsibilities

• Conduct research and analysis at the direction of Senior Management and the Analytics Team.
• Design strategies for analysis of large sets of data, including geospatial datasets.
• Assist in working through strategies for cleansing data.
• Develop financial and technical models for reporting and business intelligence tasks.
• Work hands on with large sets of real estate data and consumer data to help develop new applications, databases and data structures.
• Perform other tasks as required.

Requirements

• Undergraduate Degree or Master’s Degree in Computer Science, Engineering, Statistics, Economics, or commensurate technical experience.
• 2-3 years of experience in a technical role or analytics role (software development, data science, etc.)
• 1-2 years previous scripting experience (Python, Ruby, R, etc.).
• Demonstrated ability to manage multiple projects simultaneously, work under pressure, work independently and meet deadlines.
• Technical familiarity with analysis techniques such as machine learning and regression analysis.
• Previous experience with SQL and geospatial analysis a big plus.
• Proficient with data-centric software packages (scikit-learn, pandas, SAS, Tableau, SPSS, R, Excel).