Data Science Summer Intern
The Group: Morningstar’s Quantitative Research Group creates independent investment research and data-driven analytics designed to help investors discover relevant catalyzing insights that can be relied upon and deliver them efficiently. 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 Internship Program: Spend your summer working with an interdisciplinary team of researchers, technologists, engineers, product owners, and data scientists that focus on developing innovative models and cutting-edge investment tools. You will employ the best methodologies and techniques to large amounts of data while gaining professional insights about the quantitative research and financial product development.
You are a self-starter and inquisitive. You are always willing to learn new techniques and experiment with various technologies. You know your way around data and can work alongside our data ninjas. You will improve or build new products by implementing and developing algorithms. The synthesis of your analysis will provide valuable investment insight for individuals, advisors, and asset managers.
Minimum qualifications:
- Currently pursuing a PhD in computer science, statistics, applied math, economics, operations research or similar quantitative fields.
- Must be enrolled in a full-time degree program within the US.
- Experience with relational (MySQL, MSSQL, Athena) databases.
- Experience using scripting and statistical programming languages (Python, R, bash or similar).
Preferred qualifications:
- Expected graduation date in Fall 2018 or Spring/Summer of 2019.
- Knowledge and practical experience with machine learning, text and data mining, optimization, deep learning, and/or econometrics.
- Experience and familiarity with XML, relational, and file-based databases (MySQL, Athena, S3)
- Experience with statistical data analysis such as linear models, multivariate analysis, hypothesis testing, anomaly detection, etc.
- Experience with data visualization is a plus (e.g. Tableau, Shiny, d3)
- Experience with Big Data platforms such as Hadoop, AWS, H2O, Spark
- Strong research-oriented resume and publication records.
Morningstar is an equal opportunity employer.