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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
Experience, Skills and Qualifications
Morningstar, Inc. is a leading provider of independent investment insights in North America, Europe, Australia, and Asia. The Company offers an extensive line of products and solutions that serve a wide range of market participants, including individual and institutional investors in public and private capital markets, financial advisors and wealth managers, asset managers, retirement plan providers and sponsors, and issuers of fixed-income securities. Morningstar provides data and research insights on a wide range of investment offerings, including managed investment products, publicly listed companies, private capital markets, debt securities, and real-time global market data. Morningstar also offers investment management services through its investment advisory subsidiaries, with approximately $328 billion in AUMA as of Sept. 30, 2024. The Company operates through wholly-owned subsidiaries in 32 countries.
Job ID: 108517971
Skills:
Machine Learning, Kafka, Sql, Tensorflow, Pandas, Numpy, Gcp, Pytorch, Docker, Kubernetes, Python, AWS, LangChain, Airflow, scikit-learn
Skills:
Kubernetes, python, Tensorflow, Pytorch, aws, mlflow
Skills:
data strategies , Machine Learning, fine-tuning, AI research, training methodologies, data annotation, AI quality assurance, LLM evaluation
Skills:
Sql, AWS, Kubernetes, Python, Gcp, Docker, Machine Learning, Kafka, Spark, Llm, RAG, Generative AI models
Skills:
FastAPI, Sql, Tensorflow, Pyspark, Pandas, Pytorch, Python, Flask, XGBoost, Azure ML, Azure DevOps, scikit-learn, LightGBM
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