Morgan Stanley
Overview
Director, Software Engineer role at Morgan Stanley. Responsibilities
Design and develop natural language processing methodologies for information extraction from textual data. Utilize specialized knowledge of fixed income classes and financial documents to develop NLP models. Collaborate with internal technical stakeholders to translate complex customer requirements into tailored NLP models. Design, implement, and integrate NLP models with existing systems. Design, implement, and support scalable, reliable, high-performance services. Perform exploratory data analysis to build high-quality training and validation datasets for model training and evaluation. Apply latest advances in deep learning and NLP to improve data models, data pipelines, and data featurization. Design, implement, test, and maintain production-ready distribution of NLP components. Manage project priorities, deadlines, and deliverables. Telecommuting permitted up to 1 day per week. Compensation
Salary: Expected base pay rates for the role will be between $149,000 and $165,000 per year at commencement of employment. Base pay is individualized and part of the total compensation package, which may include commission, incentive compensation, discretionary bonuses, and other Morgan Stanley sponsored benefits. Qualifications
Bachelor’s degree in Computer Engineering, Computer Science, or a related field. Two (2) years of experience in the position offered or two (2) years in a related technology role (Manager, Associate, Analyst, or related). Experience with Python for end-to-end workflows, data collection and preprocessing for model training, and evaluation. Data analytics with NumPy and Pandas; data manipulation, cleaning, transformation, and exploratory data analysis (EDA). NLP experience including supervised and unsupervised learning for text classification, summarization, question answering, named entity recognition, and sentiment analysis. Experience with NLP toolkits (NLTK, SpaCy, Gensim) and deep learning frameworks (PyTorch, TensorFlow) for building, training, and deploying neural networks. Hugging Face Transformers for leveraging and fine-tuning pre-trained models (e.g., BERT, BART, T5). Model evaluation and hyperparameter tuning with Scikit-Learn; data visualization with Matplotlib, Seaborn, or Plotly. Web frameworks such as Flask. Knowledge of fixed-income securities and structured finance documentation for CBMS, RMBS, ABS, and CLO; ability to review and interpret credit rating reports, EDGAR forms, and exhibits. Application and Equal Opportunity
Qualified applicants: To apply, visit the Morgan Stanley careers portal and search for JR014971. EOE. Morgan Stanley is an equal opportunity employer committed to diversity and inclusion.
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Director, Software Engineer role at Morgan Stanley. Responsibilities
Design and develop natural language processing methodologies for information extraction from textual data. Utilize specialized knowledge of fixed income classes and financial documents to develop NLP models. Collaborate with internal technical stakeholders to translate complex customer requirements into tailored NLP models. Design, implement, and integrate NLP models with existing systems. Design, implement, and support scalable, reliable, high-performance services. Perform exploratory data analysis to build high-quality training and validation datasets for model training and evaluation. Apply latest advances in deep learning and NLP to improve data models, data pipelines, and data featurization. Design, implement, test, and maintain production-ready distribution of NLP components. Manage project priorities, deadlines, and deliverables. Telecommuting permitted up to 1 day per week. Compensation
Salary: Expected base pay rates for the role will be between $149,000 and $165,000 per year at commencement of employment. Base pay is individualized and part of the total compensation package, which may include commission, incentive compensation, discretionary bonuses, and other Morgan Stanley sponsored benefits. Qualifications
Bachelor’s degree in Computer Engineering, Computer Science, or a related field. Two (2) years of experience in the position offered or two (2) years in a related technology role (Manager, Associate, Analyst, or related). Experience with Python for end-to-end workflows, data collection and preprocessing for model training, and evaluation. Data analytics with NumPy and Pandas; data manipulation, cleaning, transformation, and exploratory data analysis (EDA). NLP experience including supervised and unsupervised learning for text classification, summarization, question answering, named entity recognition, and sentiment analysis. Experience with NLP toolkits (NLTK, SpaCy, Gensim) and deep learning frameworks (PyTorch, TensorFlow) for building, training, and deploying neural networks. Hugging Face Transformers for leveraging and fine-tuning pre-trained models (e.g., BERT, BART, T5). Model evaluation and hyperparameter tuning with Scikit-Learn; data visualization with Matplotlib, Seaborn, or Plotly. Web frameworks such as Flask. Knowledge of fixed-income securities and structured finance documentation for CBMS, RMBS, ABS, and CLO; ability to review and interpret credit rating reports, EDGAR forms, and exhibits. Application and Equal Opportunity
Qualified applicants: To apply, visit the Morgan Stanley careers portal and search for JR014971. EOE. Morgan Stanley is an equal opportunity employer committed to diversity and inclusion.
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