Director, Data Science Boston, MA
Job Description:
Position Description:
Manages and guides data science and data engineering elements of Artificial Intelligence (AI) projects. Understands Machine Learning (ML), Deep Learning (DL) algorithms, and Large Language Models (LLMs) both in terms of application and training ground up. Understands fundamental Natural Language Processing (NLP) and ML algorithms. Runs ML models from HuggingFace and other popular libraries. Understands different LLMs, their pros and cons, quantization of LLMs, and optimal deployment in different environments. Programs using languages -- Python and Pytorch. Works closely with business stakeholders, collects requirements, and delivers high value AI/ML solutions that drive customer and business value.
Primary Responsibilities:
• Analyzes large datasets, performs quality assurance, and ensures data quality.
• Presents the results of mathematical modeling and data analysis to management or other end users.
• Defines data requirements and gathers and validates information.
• Applies judgment and statistical tests.
• Develops and models software solutions using methodologies and approaches -- NLP, Information Retrieval, Machine Comprehension, Question Answering/Conversational AI, Reinforcement Learning, Knowledge Graph, Causal Inference, and Design of Experiment.
• Formulates and applies mathematical models and other optimizes methods to develop and interpret information that assists management with decision making, policy formulation, or other managerial functions.
• Develops and supplies optimal time, cost, or logistics networks for program evaluation, review, or implementation.
Education and Experience:
Bachelor’s degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and five (5) years of experience as a Director, Data Science (or closely related occupation) building Artificial Intelligence/Machine Learning (AI/ML) models in a financial services environment.
Or, alternatively, Master’s degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and two (2) years of experience as a Director, Data Science (or closely related occupation) building Artificial Intelligence/Machine Learning (AI/ML) models in a financial services environment.
Or, alternatively, Ph.D in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and no experience.
Skills and Knowledge:
Candidate must also possess:
• Demonstrated Expertise (“DE”) developing and evaluating supervised and unsupervised Machine Learning (ML) algorithms performing advanced statistical analytics to -- Deep Learning (DL), Large Language models, Feature Selection, Hyper-Parameter tuning, or Model optimizations -- using Python and ML libraries including scikit-learn, Tensorflow, Keras, PyTorch or HuggingFace with specific use cases on Conversational Artificial Intelligence (AI) and Dialog Systems applications within a planning, advice, and financial investments domain.
• DE designing and developing Natural Language Processing solutions to process unstructured and semi-structured text for NLP tasks – conversation AI, information retrieval, question answering, named entity recognition, or few-shot learning -- using classical NLP and ML methods.
• DE launching ML and DL models in a production environment, model and deployment optimization, and performing data and runtime profiling of the solutions to assess the efficacy of the ML and AI algorithms using platforms and tools including AWS, Kubeflow, PyTorch, Deep Java Library (DJL), or vLLM.
• DE conducting ML research in the financial domain, including conversational AI, question answering, sentiment analysis and conversational evaluation using PyTorch, Tensorflow, Transformers, or Large Language Models; and leading development efforts for complex dialog systems, including model development, task delegation, and stakeholder communication using frameworks including Scrum or Kanban.
Salary: $180,250.00 - $194,000.00 /year.
#PE1M2
#LI-DNI
Certifications:
Category:
Data Analytics and Insights
Most roles at Fidelity are Hybrid, requiring associates to work onsite every other week (all business days, M-F) in a Fidelity office. This does not apply to Remote or fully Onsite roles.
Please be advised that Fidelity’s business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.
Apply Now
Apply Now
Position Description:
Manages and guides data science and data engineering elements of Artificial Intelligence (AI) projects. Understands Machine Learning (ML), Deep Learning (DL) algorithms, and Large Language Models (LLMs) both in terms of application and training ground up. Understands fundamental Natural Language Processing (NLP) and ML algorithms. Runs ML models from HuggingFace and other popular libraries. Understands different LLMs, their pros and cons, quantization of LLMs, and optimal deployment in different environments. Programs using languages -- Python and Pytorch. Works closely with business stakeholders, collects requirements, and delivers high value AI/ML solutions that drive customer and business value.
Primary Responsibilities:
• Analyzes large datasets, performs quality assurance, and ensures data quality.
• Presents the results of mathematical modeling and data analysis to management or other end users.
• Defines data requirements and gathers and validates information.
• Applies judgment and statistical tests.
• Develops and models software solutions using methodologies and approaches -- NLP, Information Retrieval, Machine Comprehension, Question Answering/Conversational AI, Reinforcement Learning, Knowledge Graph, Causal Inference, and Design of Experiment.
• Formulates and applies mathematical models and other optimizes methods to develop and interpret information that assists management with decision making, policy formulation, or other managerial functions.
• Develops and supplies optimal time, cost, or logistics networks for program evaluation, review, or implementation.
Education and Experience:
Bachelor’s degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and five (5) years of experience as a Director, Data Science (or closely related occupation) building Artificial Intelligence/Machine Learning (AI/ML) models in a financial services environment.
Or, alternatively, Master’s degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and two (2) years of experience as a Director, Data Science (or closely related occupation) building Artificial Intelligence/Machine Learning (AI/ML) models in a financial services environment.
Or, alternatively, Ph.D in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and no experience.
Skills and Knowledge:
Candidate must also possess:
• Demonstrated Expertise (“DE”) developing and evaluating supervised and unsupervised Machine Learning (ML) algorithms performing advanced statistical analytics to -- Deep Learning (DL), Large Language models, Feature Selection, Hyper-Parameter tuning, or Model optimizations -- using Python and ML libraries including scikit-learn, Tensorflow, Keras, PyTorch or HuggingFace with specific use cases on Conversational Artificial Intelligence (AI) and Dialog Systems applications within a planning, advice, and financial investments domain.
• DE designing and developing Natural Language Processing solutions to process unstructured and semi-structured text for NLP tasks – conversation AI, information retrieval, question answering, named entity recognition, or few-shot learning -- using classical NLP and ML methods.
• DE launching ML and DL models in a production environment, model and deployment optimization, and performing data and runtime profiling of the solutions to assess the efficacy of the ML and AI algorithms using platforms and tools including AWS, Kubeflow, PyTorch, Deep Java Library (DJL), or vLLM.
• DE conducting ML research in the financial domain, including conversational AI, question answering, sentiment analysis and conversational evaluation using PyTorch, Tensorflow, Transformers, or Large Language Models; and leading development efforts for complex dialog systems, including model development, task delegation, and stakeholder communication using frameworks including Scrum or Kanban.
Salary: $180,250.00 - $194,000.00 /year.
#PE1M2
#LI-DNI
Certifications:
Category:
Data Analytics and Insights
Most roles at Fidelity are Hybrid, requiring associates to work onsite every other week (all business days, M-F) in a Fidelity office. This does not apply to Remote or fully Onsite roles.
Please be advised that Fidelity’s business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.
Apply Now
Apply Now