Quantitative Engineer Manager - Data Scientist

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

At Freddie Mac, you will do important work to build a better housing finance system and you’ll be part of a team helping to make homeownership and rental housing more accessible and affordable across the nation.

Position Overview:

Do you want to play a key role in Single-Family’s Innovation, Data Science, Engineering and Analytics (IDEA) Transformation journey? Freddie Mac’s Single-Family Division is currently seeking a curious and analytical Quantitative Engineer Manager - Data Scientist. In this position, you would be responsible for designing data processes to support industry-leading models for assessing the creditworthiness of prospective borrowers, analytics and reporting needs as a member of the MEDA (Modeling, Econometrics and Data Analytics) team. IDEA has a critical function to manage and maintain business data and identify new data sets/solutions to enabling analytics for policy refinements, model development and portfolio reporting using state of the art techniques such as Machine Learning, Artificial Intelligence and Big Data/Cloud Technologies. We are looking for a self-starter, hardworking explorer and Data enthusiast to help us establish Artificial Intelligence and Machine Learning best practices, who will partner across Freddie Mac teams to create solutions to solve challenging business problems. Apply now and learn why there’s #MoreAtFreddieMac!

**This position can be performed currently from a remote location in the U.S. but will require presence in a Freddie Mac office in the future.***

Our Impact:

Freddie Mac’s Single-Family Modeling and Analytics team is an organization that builds models and analytics to advance the strategies of the Single-Family business so that Freddie Mac can help get people into homes they can afford and keep. Our models are behind many key business initiatives at Freddie Mac such as Credit Risk Transfer, Portfolio Management, Collateral Valuation, Risk Management, Affordable Housing, Mortgage Fair Lending. We are guided and empowered by several core principles, including the need to leverage the full team and that cross-disciplined approaches are far more likely to produce breakthrough models. We recognize that to be at our best we need to build an organization that allows individuals to learn about and participate in a variety of models and modeling techniques.

In our team, candidates work with enthusiastic and collaborative professionals with a diverse set of backgrounds in econometrics, statistics, machine learning and analytics to support and advance Innovative analytics and develop cutting-edge solutions to convert insights into actions. Applying their quant skills, candidates routinely extract, understand and analyze data in our wide repository of sources, and further produce insights and build models that will inform Freddie Mac’s decisions on our mortgage portfolio while working across all parts of Single-Family business groups including, Business Leadership, Product Owners, Data Owners and IT Partners. Candidates have the opportunity to perform a wide range of analyses with high impact on management decisions.

Your Impact:

• Build and manage sustainable partnerships with business and technology partners to ensure that their needs are met with IDEA services.
• Strive to bring better customer experience with every engagement on major business/technology initiatives.
• Solve demanding and complicated business problems by applying modern technology and best practices to the engineering of large data sets.
• Lead Text Analytics and Image Processing R&D efforts and influence business and IT teams to drive decisions.
• Responsible for designing and implementing AI/ML systems/models as part of our data engineering framework such as converting free form text into insights.
• Working with IT partners to operationalize the AI/ML models by building ML Ops platform that adheres to model governance.
• Collaborate with team members and interact across organizational lines to meet business objectives.
• Solid understanding of business & systems needs and detail requirements to ensure business requirements are translated correctly.
• Familiarity with Agile Methodology.
• Experience managing junior data scientists and matrixed resources.
• Solid understanding of data architecture, data cleansing, metadata management principles.
• Collaborate with business SMEs and technical SMEs to develop features.
• Works on issues of diverse scope where analysis of situation or data requires evaluation of a variety of factors, including an understanding of current data environments and processes.
• Develop Model 2 Service solutions with microservices.
• Works under limited direction. Independently resolves and develops approach to solutions.
• Would be required to engage using SAS, SQL, Python, R, PySpark, PIG, HIVE scripts to filter/map/aggregate data in a variety of structured and unstructured formats(e.g. XMLs, CSVs, Fixed length, JSONs and PDFs).
• Must be able to handle multiple priorities and meet deadlines.

Qualifications:

• Doctorate/Master’s degree (or Bachelor’s degree with equivalent work experience and evidence of exceptional ability) in a quantitative field (e.g., Statistics, Data Science, Quantitative Finance, Computer Science, Mathematics, Industrial Engineering or related fields)
• 8+ years of work experience in Machine Learning, Artificial Intelligence, Data analytics, Data engineering, Data science or related fields;
• 5+ years of experience in people management
• Strong predictive data modeling experience is required, with proven application in applying decision trees, regression analysis, deep neural networks, clustering, machine learning, NLP and other data mining techniques
• Competency or certifications with SAS, SQL, Python, R or other data mining and analytical tools
• Ability to serve as mentor to more junior members of team
• Mortgage and operations research experience strongly preferred
• Familiar with business intelligence tools such as Tableau and MicroStrategy
• Ability to manage multiple high priority demands simultaneously and achieve success in situations with high degrees of variation and complexity
• Experience handling multiple projects under a program management.
• Solid understanding of Data Platforms such as Databases, Non-SQL Data Repositories, and Big Data and ML platforms like Tensor flow.
• Foundational knowledge on AWS Cloud Platforms, AWS AI/ML packages and Microservices.
• Experience with database, data model and data warehouse concepts.

Keys to Success in this Role:

• Ability to think critically and logically.
• Curiosity not just about the data, but also about the business.
• Strong predictive data modeling experience and solid skills.
• Ability to collaborate with people from a diverse set of backgrounds.
• Solid communications skills – verbal and written.
• Detail oriented and excellent organization skills.
• Strong quantitative, data analytics, analytical, and problem-solving skills.
• Self-starter with desire to not only execute on existing objectives but also identify new ways to push Freddie Mac forward.
• A passion for machine learning and results-oriented attitude.