Role: Associate Software Engineer, Quantitative Research
Job Description
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. 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 Software Engineer, you will responsible for developing data intensive analytics tools and workloads built on Big Data and Python. Develop analytics workloads to ensure the timely and accurate delivery of insights. Be Agile and enforce Software Engineering best practices for analytics workloads that are deployed as part of Morningstar Quant Research Infrastructure. The Software Engineer will work closely with Quant analysts, Data Scientists, QA Engineers, DevOps and Data Engineers to deliver on these applications.
You are an individual who possesses strong technical skills, loves cloud technology, and has a passion for working in Investment Management / Fintech Space. You also enjoy working with technical teams on complex problems and are always looking to improve yourself and others around you.
This position reports to the Manager of the Quantitative Research team.
Responsibilities:• Implement models in Python per specifications provided by Quant Analyst and Data Scientists, Suggest best practices for high performance and automated execution• Automate advanced data aggregation methodologies for stand-alone execution in cloud.• Implement data enrichment logic; implement automations to identify deviations in input data• Manage development tasks in a fast-paced/ agile environment to ensure they are completed on time with attention to delivering high quality results.• This is primarily a coding role and not a statistical modeling role.
Requirements:• 2-3 years' experience working/coding in Python related projects.• Experience with Python packages as Pandas, Scipy, Numpy, Sklearn using OOPS framework.• Experience developing and managing components build on Big Data (Spark).• Experience writing unit tests for Python.• Added plus is experience managing data intensive applications (Big Data) & machine learning systems.• Knowledge of AWS/Cloud ecosystem is added plus.• Experience working with large, complex tables under Postgres, SQL Server.• Comfortable with Linux with ability to write small scripts in Bash/Python. Ability to grapple with log files and Unix processes.• Experience working under Agile software engineering environment.• Familiarity with mutual fund, fixed income, and equity data is a plus.
Morningstar is an equal opportunity employer.
Morningstar's hybrid work environment gives you the opportunity to work remotely and collaborate in-person each week. We've found that we're at our best when we're purposely together on a regular basis, at least three days each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.
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What We Do
At Morningstar, we believe in building great products in-house in a highly collaborative, agile environment where we focus on technical excellence, the user experience, and continuous improvement. Our technologists represent a range of skills and experience levels, but they all view their work as a craft and push technology’s boundaries.
Why Work With Us
Imagining big things is in our blood -- it's transformed us from a company with just a few employees in 1984 to a leading independent investment research company with a worldwide presence today. As of April 2020, we acquired Sustainalytics to drive long-term meaningful outcomes for investors in the ESG space. Join us on this exciting journey!
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Morningstar Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.