Job Overview
PitchBook's Senior Machine Learning Engineer is responsible for using machine learning, statistical modeling, and natural language processing (NLP) to collect a high-volume of data for the PitchBook Platform and surface insights for the capital markets. This role will also serve as a resource and mentor for junior members of the team. A strong motivation to succeed is critical and everyone has the opportunity to shape the long-term direction of our team.
Team Overview
PitchBook's Data Science and Machine Learning team has a clear mission: leverage cutting-edge machine learning and cloud technologies to automatically research millions of private companies and process hundreds of millions of news articles. Our team is also responsible for building services to improve the PitchBook Platform's search and discovery capabilities.
Outline of Duties and Responsibilities
- Apply NLP and Machine Learning: Analyze and extract features from large amounts of unstructured data, determine most relevant features, and use appropriate algorithms to drive insight into the data.
- Extract Insights from Textual Data: Analyze unstructured data such as articles and conversations to identify unique signals of company performance, aiding market trend prediction.
- Collaborate Efficiently: Partner with Data Scientists, Product and Engineering teams to automate processes for large-scale data, improving data management, and analysis.
- Stay Informed and Lead: Stay updated on industry trends in Data Science and ML, actively contributing to the development of best practices and thought leadership.
- Support Company Vision: Share our company's values and foster a positive work culture.
- Participate in Initiatives: Engage in company projects to contribute to overall success.
Experience, Skills and Qualifications
- Bachelor's degree in Computer Science, Machine Learning, Statistics or related field.
- 5+ years of experience leveraging the above mentioned skills in a production environment.
- Demonstrated experience with natural language processing.
- Extensive experience with Python and OOP Framework.
- Demonstrated experience in using SQL for data extraction.
- Strong communication and data presentation skills.
- Strong problem solving ability.
- Ability to work autonomously and come up with solutions to own problems and problems of others.
- Ability to communicate complex analysis in a clear, precise, and actionable manner.
- Experience working closely a with software development team(s) a plus.
- Financial services, investment, banking, VC and/or PE knowledge is preferred, but not mandatory.
Morningstar is an equal opportunity employer
Working Conditions
The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.
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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.