Marketing Lead & Sales Optimization Products to Improve Follow-up Efficiency - In collaboration with the Sales Operations team, the Data Scientist will design algorithms that help our Senior Living Advisors follow up with the right families at the right time. This project involves writing prediction algorithms that balance accuracy with human interpretability. It also involves designing experiments to test the impact of competing algorithms on customer success relative to each other and a control group. Going forward, future projects will include all phases of our sales funnel.
Senior Living Cost Index - A Place for Mom built the public-facing Senior Living Cost Index to help families understand the median cost of different types of senior housing and care in over 3,000 cities in America. The tool is driven by a set of hedonic pricing models (based on individual-level senior housing and care transactions plus socio-demographic and geographic data) and repeat-sales models of price growth. The Data Scientist will continuously improve these models, communicating their results to the public and to reporters via press interviews. The Data Scientist will also work with designers to improve the user interface for the tool.
Industry-Facing Data Product - We are using our massive transaction database to build an industry-facing web app and data product that measures and forecasts senior housing and care demand. Currently in alpha testing phase, this product will be continuously improved and expanded by the Data Scientist. Currently, the web app is implemented in Shinyapps.io, and is driven by prediction and forecasting models built in the R programming language. The Data Scientist will also communicate with potential consumers of the data product, including large real estate investment trusts who invest in senior living communities, and our senior living community partners.
Customer Insights - A Place for Mom has recently appended a massive amount of third-party data to our database of consumers who inquire about senior housing and care. The Data Scientist will dig into this third-party data to assess its potential value to the company, whether it be through the development of consumer segmentation models, or the identification of third-party-sourced variables that could improve existing expected revenue and move-in prediction algorithms.
Data Journalism - The Data Scientist will perform some ad hoc analyses to support public relations efforts, and help our content marketers and public relations consultants pitch newsworthy insights gathered through ongoing research projects.
Academic Collaboration - Academics and top-tier research institutions have expressed interest in using our unique data to study the decisions families make about senior housing and care. The Data Scientist will help to foster these collaborative relationships and support third-party researchers in understanding how to use our data effectively. These efforts may include co-authorship on peer-reviewed journal articles.