Senior Data Scientist #103

Homes.com
Homes.com

Job Overview

Senior Data Scientist for Homes.com, Inc. to work at our Norfolk, VA loc. Lead efforts to ID operations to leverage data + new data sources to solve challenges associated with growth. Lead analytical + machine learning projects to improve business performance (e.g., improved customer satisfaction, increased op efficiency, improved revenue generation, + other business outcomes). Lead extraction, integration, + analysis of data from heterogeneous sources to create insights + support recs to internal stakeholders. Navigate data infrastructure + implement ETL jobs so analysts + internal customers have access to data required for KPis + Bl reports. ID, research, + recommend internal process improvements such as automating manual process, optimizing data delivery, improving data vision. Design, create, implement, + maintain data pipelines, analytic workflows, + machine learning pipelines. Lead deployment of data science prods (e.g., quant/stat analyses + machine learning model dev, AlB tests, ETU pipeline job failure alerts, monitor + eval model performance/data quality) to prod environments. Coordinate + contribute to design, implementation, maintenance, + growth of data lake + data warehouse serving as central data clearinghouse for all business analytics needs. Collab with Sales, Strategy + Finance, Technology, + Business Development teams to lead development + implement of new information services. Mentor Junior data scientists + perform ad hoc analysis. May undergo background checks incl drug screen and ref checks. Must have Bachelor in Mathematics, Statistics, Computer Science, or related field and 5 years relevant experience in data analysis or Master’s in Mathematics, Statistics, Computer Science, or related field and 2 years relevant experience in data analysis. Also requires the following skills (2 years experience) in: using data science tools including R, Python, MLib, Apache Spark; accessing data stores including RDBMS, NoSQL, APIs/Webservices; large quantities of data and big data technology; writing high-quality and scalable code and integrating with version control systems; building complex analytical models and presenting results to stakeholders. Any suitable combination of education, training, or experience is acceptable.

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