Freedom Mortgage is looking to bring advanced analytics and predictive modeling best practices to the industry
Requirements
- Extensive knowledge and work experience (3+ years) in predictive modeling, classification, clustering, machine learning, data mining, and optimization techniques in the fields of finance, mortgage, banking, or relevant industries
- Expert knowledge and experience (3+ years) in R, Python, SAS, and/or other analytical tools
- Good working knowledge of SQL; Experience in PL/SQL and stored procedures
- Familiarity with relational databases such as Oracle, SQL Server, MySQL
- Knowledge and experience in MapReduce, Hadoop, Hive/Pig, and NoSQL
- Experience in visualization tools like Tableau, QlikView, or Spotfire
- Technique Skills required: R, Python, SAS, SAS EM, KnowledgeSeeker - Angoss /or other analytical tools, Oracle, SQL Server, PL/SQL
Responsibilities
- Design and develop machine learning models and data mining analysis in multiple fields such as Customer Behavior Analysis/Prediction, Marketing, Operational Optimization, Risk Management, Customer Attrition Prediction, Loan Fallout Prediction, etc.
- Drive the collection of new data and the refinement of existing data sources
- Conduct analytics and modeling with structured and unstructured data
- Visualize complex data and findings in the format of business tables, graphs, and dashboards
- Interpret and explain analytical results to other team members
- Evaluate external analytical models
- Recommend realistic solutions using sound judgment and business knowledge
Other
- Bachelor’s Degree or higher degree in statistics, mathematics, computer science, and engineering or a relevant science or engineering field. Master’s degree preferred
- Ability to communicate data interpretation and other technical issues to the business community
- Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
- Ability to deliver results under and meet aggressive timelines
- Ability to read, analyze, and interpret general business periodicals, professional journals, technical procedures, or government regulations
