Point72's Cubist team is seeking an NLP Engineer to build and train deep learning models for large-scale unstructured datasets. The role involves analyzing and evaluating new data sources, engaging with vendors, and presenting findings to Portfolio Managers. You will research efficient data management/retrieval techniques and propose potential applications of datasets to support investment teams. Strong Python, SQL, and practical experience with modern language model architectures (TensorFlow/PyTorch) are required.
We are looking for a motivated and skilled NLP Engineer with experience in deep learning frameworks. This position is ideal for candidates who are eager to grow their skills in the financial industry and make a significant impact.
Responsibilities:
Build start-of-the-art deep learning models to process large scale unstructured datasets.
Engage with vendors to understand characteristics of datasets.
Analyze datasets to generate descriptive statistics and propose potential applications of data.
Conduct preliminary research and evaluation on the datasets for presentation to Portfolio Managers.
Research new technologies for efficient data management and data retrieval.
Requirements:
PhD or Master’s degree in computer science, data science, statistics or other quantitative discipline. Bachelor's degree with extensive relevant work experience will also be considered.
At least 3 years of experience in NLP, computer vision, speech, or a related field.
Extensive experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
In-depth understanding of the architectures of modern language models, with practical experience in model implementation and training.
Excellent coding skills in Python.
Programming skills in SQL.
Experience working with large data sets.
Strong oral and written communication skills.
Strong team player.
Financial industry experience preferred but not required.
Candidates with top machine learning conference papers (e.g., NeurIPS, ICLR, ICML, ACL, EMNLP, NAACL) are preferred.
Commitment to the highest ethical standards.
The annual base salary range for this role is $100,000-$125,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
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Description:
\n
We are looking for a motivated and skilled NLP Engineer with experience in deep learning frameworks. This position is ideal for candidates who are eager to grow their skills in the financial industry and make a significant impact.
Responsibilities:
\n
Build start-of-the-art deep learning models to process large scale unstructured datasets.
Engage with vendors to understand characteristics of datasets.
Analyze datasets to generate descriptive statistics and propose potential applications of data.
Conduct preliminary research and evaluation on the datasets for presentation to Portfolio Managers.
Research new technologies for efficient data management and data retrieval.
Requirements:
\n
PhD or Master’s degree in computer science, data science, statistics or other quantitative discipline. Bachelor's degree with extensive relevant work experience will also be considered.
At least 3 years of experience in NLP, computer vision, speech, or a related field.
Extensive experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
In-depth understanding of the architectures of modern language models, with practical experience in model implementation and training.
Excellent coding skills in Python.
Programming skills in SQL.
Experience working with large data sets.
Strong oral and written communication skills.
Strong team player.
Financial industry experience preferred but not required.
Candidates with top machine learning conference papers (e.g., NeurIPS, ICLR, ICML, ACL, EMNLP, NAACL) are preferred.
Commitment to the highest ethical standards.
The annual base salary range for this role is $100,000-$125,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
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Point72's Cubist team is seeking an NLP Engineer to build and train deep learning models for large-scale unstructured datasets. The role involves analyzing and evaluating new data sources, engaging with vendors, and presenting findings to Portfolio Managers. You will research efficient data management/retrieval techniques and propose potential applications of datasets to support investment teams. Strong Python, SQL, and practical experience with modern language model architectures (TensorFlow/PyTorch) are required.
We are looking for a motivated and skilled NLP Engineer with experience in deep learning frameworks. This position is ideal for candidates who are eager to grow their skills in the financial industry and make a significant impact.
Responsibilities:
Build start-of-the-art deep learning models to process large scale unstructured datasets.
Engage with vendors to understand characteristics of datasets.
Analyze datasets to generate descriptive statistics and propose potential applications of data.
Conduct preliminary research and evaluation on the datasets for presentation to Portfolio Managers.
Research new technologies for efficient data management and data retrieval.
Requirements:
PhD or Master’s degree in computer science, data science, statistics or other quantitative discipline. Bachelor's degree with extensive relevant work experience will also be considered.
At least 3 years of experience in NLP, computer vision, speech, or a related field.
Extensive experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
In-depth understanding of the architectures of modern language models, with practical experience in model implementation and training.
Excellent coding skills in Python.
Programming skills in SQL.
Experience working with large data sets.
Strong oral and written communication skills.
Strong team player.
Financial industry experience preferred but not required.
Candidates with top machine learning conference papers (e.g., NeurIPS, ICLR, ICML, ACL, EMNLP, NAACL) are preferred.
Commitment to the highest ethical standards.
The annual base salary range for this role is $100,000-$125,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
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Description:
\n
We are looking for a motivated and skilled NLP Engineer with experience in deep learning frameworks. This position is ideal for candidates who are eager to grow their skills in the financial industry and make a significant impact.
Responsibilities:
\n
Build start-of-the-art deep learning models to process large scale unstructured datasets.
Engage with vendors to understand characteristics of datasets.
Analyze datasets to generate descriptive statistics and propose potential applications of data.
Conduct preliminary research and evaluation on the datasets for presentation to Portfolio Managers.
Research new technologies for efficient data management and data retrieval.
Requirements:
\n
PhD or Master’s degree in computer science, data science, statistics or other quantitative discipline. Bachelor's degree with extensive relevant work experience will also be considered.
At least 3 years of experience in NLP, computer vision, speech, or a related field.
Extensive experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
In-depth understanding of the architectures of modern language models, with practical experience in model implementation and training.
Excellent coding skills in Python.
Programming skills in SQL.
Experience working with large data sets.
Strong oral and written communication skills.
Strong team player.
Financial industry experience preferred but not required.
Candidates with top machine learning conference papers (e.g., NeurIPS, ICLR, ICML, ACL, EMNLP, NAACL) are preferred.
Commitment to the highest ethical standards.
The annual base salary range for this role is $100,000-$125,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
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