The Group: Morningstar’s Quantitative Research Group creates independent investment research and data-driven analytics designed to help investors and Morningstar achieve better outcomes by making better decisions. We utilize statistical rigor and large data sets to inform the methodologies we develop. Our research encompasses hundreds of thousands of securities within a large breadth of asset classes including equities, fixed income, structured credit, and funds. Morningstar is one of the largest independent sources of fund, equity, and credit data and research in the world, and our advocacy for investors’ interests is the foundation of our company.
The Role: As a Senior Engineer, you will be a leading contributor in the implementation and maintenance of statistical software applications, research databases, risk modelling, and other data products. This role requires significant interaction with both upstream and downstream stakeholders across Technology, Data, Products, Sales/Service, and Research.
You will assist in the transition of approved research products from the prototype phase to fully-fledged, scalable, and client-facing services. Often, these services must be integrated into Morningstar’s platform of financial products, such as Direct, so that our clients can use these software tools in the investment decision-making process.
We are looking for an individual who possesses strong technical development skills, an ability to follow analyst requirements and technical specifications for robust code, a solid quantitative mindset, and a strong understanding of finance.
• Develop and deploy production applications that incorporate numerical techniques such as linear algebra, machine learning, statistics, and optimization.
• Collaborate with the fixed income methodology experts to build out a comprehensive fixed income risk modelling solution.
• Design clear system specifications and maintain a robust development environment via strong documentation and version control.
• Find creative solutions to complex development problems using all technologies at your disposal, especially big data and cloud technologies.
• Recommend improvements to existing development practices and processes.
• Minimum of 5 years of experience in software engineering.
• An advanced degree in engineering, computer science, statistics or related field.
• Experience Python or C#/.NET is essential. some C/C++ skills are highly desirable. Experience with Python packages like pandas, scikit-learn, tensorflow, numpy is a plus.
• Experience developing APIs and microservices hosted in the cloud.
• Familiarity with DevOps tools (e.g. Splunk, Git, uDeploy, Jenkins, Control-M).
• Familiarity with Agile software engineering practices.
• Familiarity with back-end XML, relational, and file-based databases (e.g. SQL, Postgres, Redshift, Netezza, HDFS).
• Experience with UNIX/Linux including basic commands and shell scripting.
• Experience developing and deploying solutions using services in the Amazon AWS ecosystem (Lambda, EC2, RDS, EMR) is a plus.
• Experience with the Hadoop stack (MapReduce, Pig, Hive, Nifi, Spark) is a plus.
• Experience with at least one statistical modeling language (e.g. R, MATLAB, Python) is a plus.
• Experience designing, developing, and implementing ETL is a plus.
• Intermediate knowledge of statistical methods is a plus.
• Familiarity with common data cleaning and munging techniques is a plus.
• Familiarity with automation tools such as Puppet or Chef is a plus.
• Familiarity with statistical software, linear algebra, optimization, and information visualization is a plus.
• Familiarity with mutual fund, fixed income, and equity data is a plus.
• Progress towards a CFA is a plus.
• Strong financial engineering background is a major plus.
• Intermediate knowledge of Fixed income is a plus.
• Intellectual curiosity for the world of quantitative research.
Morningstar is an equal opportunity employer.