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Leading Macro Hedge Fund - Macro Econometrics Algorithm Developer (Real-Time NLP Focus) - New York
This role centers on the development of real-time NLP algorithms, with a strong emphasis on applying advanced econometric techniques to macroeconomic data. You'll design and implement data pipelines to ingest and process diverse data sources, focusing on the econometric modeling of real-time data for predictive insights. A key responsibility involves translating these analyses into actionable investment strategies, leveraging sophisticated econometric models such as Factor Models, Panel Data Models, and Time Series Models.
The ideal candidate will possess a deep understanding of econometric theory and its application to financial markets, evidenced by a top-tier GPA from a Master’s degree program in Econometrics, Economics, obtained from a top-tier university. They will have 2-6 years of experience within a bank, hedge fund, or central bank.
Skills:
Send your resume to James@njf.com
This role centers on the development of real-time NLP algorithms, with a strong emphasis on applying advanced econometric techniques to macroeconomic data. You'll design and implement data pipelines to ingest and process diverse data sources, focusing on the econometric modeling of real-time data for predictive insights. A key responsibility involves translating these analyses into actionable investment strategies, leveraging sophisticated econometric models such as Factor Models, Panel Data Models, and Time Series Models.
The ideal candidate will possess a deep understanding of econometric theory and its application to financial markets, evidenced by a top-tier GPA from a Master’s degree program in Econometrics, Economics, obtained from a top-tier university. They will have 2-6 years of experience within a bank, hedge fund, or central bank.
Skills:
- Econometric Modeling (Factor Models, Panel Data Models, Time Series Models, Generalized Linear Models, Linear Regression)
- Python Proficiency (NumPy, Pandas, Scikit-learn, Statsmodels, Stan)
- Natural Language Processing Libraries (NLTK, spaCy, Transformers).
- Natural Language Processing Algorithms: Sentiment analysis algorithms, Topic modeling (LDA), Word embeddings, Named entity recognition
- Data Pipeline Design and Implementation (ETL, API integration for data retrieval)
- Financial Market Data Analysis (including alternative data)
- Time Series Data Structures: Efficient storage and manipulation of time-stamped data, crucial for real-time analysis. Examples include specialized time series databases or optimized in-memory representations.
- Queues and Stacks: Used for managing incoming data streams and processing them in a specific order, essential for real-time data pipelines.
- Hash Tables: For rapid lookups and data retrieval, vital for processing large datasets and identifying patterns in real-time.
- Trees (e.g., Tries): Useful for efficient text processing and searching, particularly in NLP applications involving real-time analysis of textual data.
- Graphs: To represent relationships between data points, enabling the analysis of complex networks and dependencies in financial markets.
- Priority Queues: For managing and processing events or data points based on their priority, critical for real-time decision-making in trading.
Send your resume to James@njf.com
