Quantitative Analytics Professional

Freddie Mac
McLean, VA
Oct 08, 2019
Oct 15, 2019
Full Time
As a Quantitative Analytics professional on the House Price Modeling Team, you will work with enthusiastic and collaborative professionals with diverse quantitative backgrounds to design and implement solutions that solve new business initiatives around automation of loan manufacturing, model and/or monitor local and national residential housing trends and provide valuation on distressed property. You will accomplish this by utilizing statistics, machine learning methods, and advanced visualization techniques in combination with vast amounts of housing and mortgage data.

Your Work Falls into Three Primary Categories

Data Extraction and Manipulation
  • Extracting and combing structured and semi-structured data from databases (oracle, db2, HIVE) and standard file systems
  • Prepare dash boards that summarize data properties and trends
  • Prepare data for model building

Model Monitoring and Documentation
  • Build processes for analyzing model input and output for performance tracking
  • Build visualizations that summarize model performance
  • Prepare presentations and memos that communicate analytical results to key business stakeholders

Basic Responsibilities
  • Writing code
  • Build and analyze models
  • Research new modeling techniques
  • Research existing and new sources of data


  • Master's degree in statistics, quantitative finance or a related quantitative field.
  • Coursework or work experience applying predictive modeling techniques from data science, statistics, machine learning, and econometrics to large data sets. Qualifying coursework may include-but is not limited to-data science, statistics, machine learning, optimization, numerical analysis, scientific programming, computational methods, supervised learning, unsupervised learning, text mining, and image analysis.
  • Coursework or work experience writing computer programs to implement data science pipelines and predictive algorithms. Programming languages may include-but are not limited to-Python, R, SQL, Java, SAS, and MATLAB.
  • Coursework or work experience using technologies for manipulating structured and unstructured big data. Big data technologies may include-but are not limited to-Hadoop, Hive, Pig, Spark, relational databases, and NoSQL.

Keys to Success in this Role
  • Desire to work in a collaborative environment and approach developing projects with a customer centric focus
  • Individuals must be motivated to get out of their comfort zone and explore new ways of solving traditional problems
  • Demonstrate skills with moderate supervision and guidance from management

Top 3 Personal Competencies to Possesses
  • Partnership: Build trust and strong partnerships through my own and my team's actions
  • Customer Focus (Internal and External): Personally engage with customers to learn their needs
  • Growth and Development: Know or learn what is needed to deliver results and successfully compete

Preferred Skills

Preferred Skills
  • Familiarity with SAS
  • Familiarity with Amazon Web Services
  • Familiarity with Hadoop ecosystem and Spark
  • Familiarity with Structured Query Language (SQL)
  • Familiarity with code versioning and management using GIT

Today, Freddie Mac makes home possible for one in four home borrowers and is one of the largest sources of financing for multifamily housing. Join our smart, creative and dedicated team and you'll do important work for the housing finance system and make a difference in the lives of others. Freddie Mac is an equal opportunity and top diversity employer. EOE, M/F/D/V.