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. Morningstar’s Research group provides independent analysis on individual securities, funds, markets, and portfolios. The Research group also provides data on hundreds of thousands of investment offerings, including stocks, mutual funds, and similar vehicles, along with real-time global market data on millions of equities, indexes, futures, options, commodities, and precious metals, in addition to foreign exchange and Treasury markets.
As a Data Scientist, you will be a leading contributor in the implementation of Artificial Intelligence (AI) within Data Collections software applications. This role requires significant interaction with both upstream and downstream stakeholders across Technology, Data and Research.
The Data Scientist will transition approved Data Collections AI products from a prototype phase to a fully-fledged, scalable, and consumer service. Often, these services must be integrated into Morningstar’s platform of financial products, 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, and a passion for investment research.
This position reports to the Tech Manager of the Data Collections AI team.
- Understand business needs to design and implement machine learning solutions to automate data collection processes.
- Collaborate with peer engineering teams and downstream data analysts to continuously and iteratively improving workflows and data storage practices.
- Follow good development practices, innovative frameworks and technology solutions that help business move faster, e.g., implementing automated model retraining and deployment.
- Contribute to brainstorming and help other team members in their projects.
- Prepare written reports or power point slides in English.
- 5+ years of experience with implementing machine learning solutions
- Familiar with NLP related projects, e.g., text classification, NER, machine translation etc.
- Experienced in implementing cutting-edge NLP models, e.g., BERT, RoBERTa, XLNet, etc.
- Fluent with either TensorFlow or PyTorch.
- Experienced in SQL and familiar with common data storage formats, e.g., HTML, XML, json etc.
- Fluent with Python (and its packages, e.g., pandas, numpy) and experienced in data cleaning and munging techniques.
- Strong independent analytical skills and ability to keep improving model performance.
Intermediate knowledge of statistical methods is desirable
- An advanced degree in computer science, statistics or related fields is preferred.
- Familiarity with Computer Vision is preferred, e.g., object detection, object segmentation etc.
- Familiarity with statistical models, data analytics, and data visualization is a plus.
- Familiarity with creating solutions in Amazon AWS ecosystem (Lambda, EC2, SageMaker) is a plus.
- Familiarity with mutual fund, fixed income, and equity data is a plus.
- Fluent in both oral and written English.
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