Software Engineer Professional, Financial Engineering

Freddie Mac; McLean (VA); On-site; USD 109,000 - 163,000; Full time

Job summary

Freddie Mac in McLean, Virginia is seeking a Software Engineer Professional to build production systems for data science and ML on large data sets. You will develop Python-based data transformations, expose models as web services with Flask, and deploy to AWS EKS.

You will optimize Python code, write automated tests, and review peers' work. Requires 2–4 years Python experience, a Master’s degree in a related field, and hands-on experience with microservices, Docker, Gradle, Jenkins, Git and

Qualifications

• 2–4 years of Python development experience.
• Master’s degree in Computer Science, Computational Finance or related quantitative field.
• Experience building production systems for business-critical processes.
• Experience with Gradle, Jenkins, Git and Docker.
• Experience with large microservice architectures and container orchestration.
• Experience with MSSQL and MySQL relational databases.
• Experience writing automated unit, integration, regression, performance and acceptance tests.
• Solid understanding of software design principles.

Responsibilities

• Implement new models and data transformations using Python-based technologies (PySpark, Pandas).
• Expose models as web services using Flask and deploy to AWS EKS.
• Optimize Python code to reduce runtime and memory usage.
• Write high-quality automated tests to validate code.
• Peer review colleagues’ code and assist with design and implementation challenges.

Skills

Python

PySpark

Pandas

Flask

AWS EKS

Docker

Gradle

Jenkins

Git

MSSQL

MySQL

Education

Master’s degree in Computer Science or related field

Tools

Gradle

Jenkins

Git

Docker

AWS EKS

Job description

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose.

Position Overview

Are you interested in using your software engineering skills to build numerical systems that enable machine learning and analytics on large data sets? Financial Engineering is seeking a Software Engineer Professional to develop production systems that involve data science and machine learning. We are looking for a creative and talented individual who loves to code.

Our impact

• We partner with the Single-Family Collateral Modeling team which is responsible for the firm’s Automated Valuation Model
• We build systems to make their models, data, and analytics available for business use
• We ensure that our systems are robust, scalable and fault-tolerant

Your impact

• Implement new models and data transformations using Python based technologies such as PySpark and Pandas
• Implement and expose model as web service API using Flask and deploy web services to AWS EKS
• Optimize Python code to reduce runtime and memory usage
• Write high quality automated tests to validate your code
• Peer review other team member’s code and help them with design and implementation challenges

Qualifications

• At least 2-4 years of experience developing in Python
• Master’s degree in Computer Science, Computational Finance or a directly related quantitative field.
• Experience building production systems for business-critical processes
• Experience with building and integrating tools, including knowledge of Gradle, Jenkins, Git and Docker.
• Experience developing with large microservice based architectures, container orchestration frameworks.
• Demonstrated experience with relational databases including MSSQL, MySQL
• Experience writing automated unit, integration, regression, performance and acceptance tests
• Solid understanding of software design principles

Keys to Success in this Role

• Passionate about hands-on software development
• Strong collaboration and communication skills (both written and verbal), including interacting with data scientists on technical topics
• Desire to continuously improve the technical quality and architecture of our systems to respond to business needs
• Ability to quickly learn, apply and deploy new technologies to solve emerging problems

Current Freddie Mac employees please apply through the internal career site.

We consider all applicants for all positions without regard to gender, race, color, religion, national origin, age, marital status, veteran status, sexual orientation, gender identity/expression, physical and mental disability, pregnancy, ethnicity, genetic information or any other protected categories under applicable federal, state or local laws. We will ensure that individuals are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

A safe and secure environment is critical to Freddie Mac’s business. This includes employee commitment to our acceptable use policy, applying a vigilance-first approach to work, supporting regulatory mandates, and using best practices to protect Freddie Mac from potential threats and risk. Employees exercise this responsibility by executing against policies and procedures and adhering to privacy & security obligations as required via training programs.

CA Applicants: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Time-type:Full time

FLSA Status:Non-Exempt

Freddie Mac offers a comprehensive total rewards package to include competitive compensation and market-leading benefit programs. Information on these benefit programs is available on our Careers site.

This position has an annualized market-based salary range of $109,000 - $163,000 and is eligible to participate in the annual incentive program. The final salary offered will generally fall within this range and is dependent on various factors including but not limited to the responsibilities of the position, experience, skill set, internal pay equity and other relevant qualifications of the applicant.