Senior Machine Learning Engineer - NLP

Role Overview: As a Senior Machine Learning Engineer at PitchBook, your role involves utilizing machine learning, statistical modeling, and natural language processing (NLP) to gather a large volume of data for the PitchBook Platform and uncover insights for the capital markets. You will also play a vital role as a mentor for junior team members, shaping the long-term direction of the team with your strong motivation to succeed. Key Responsibilities: - Applying NLP and Machine Learning techniques to analyze and extract features from vast amounts of unstructured data, identifying relevant features, and leveraging suitable algorithms to gain insights. - Extracting insights from textual data like articles and conversations to recognize unique signals of company performance, aiding in market trend prediction. - Collaborating efficiently with Data Scientists, Product, and Engineering teams to automate processes for large-scale data, enhancing data management and analysis. - Staying informed about industry trends in Data Science and ML, actively contributing to the development of best practices and thought leadership. - Supporting the company's vision by embracing its values and cultivating a positive work culture. - Participating in company initiatives to contribute to overall success. Qualifications Required: - Bachelor's degree in Computer Science, Machine Learning, Statistics, or a related field. - 5+ years of experience applying machine learning, statistical modeling, and NLP in a production environment. - Demonstrated expertise in natural language processing. - Extensive experience with Python and OOP Framework. - Proficiency in using SQL for data extraction. - Strong communication and data presentation skills. - Strong problem-solving abilities. - Ability to work autonomously and provide solutions to your own problems as well as those of others. - Capability to communicate complex analysis clearly, precisely, and in an actionable manner. - Experience collaborating closely with software development teams is a plus. - Knowledge in financial services, investment, banking, VC, and/or PE is preferred but not mandatory.,