Position Description:
Designs, develops, and implements artificial intelligence (AI)/machine learning (ML) mathematical models for production business use cases, including curation and pre-processing of large data sets/sources, feature engineering, experimentation, as well as model performance monitoring. Structures project work, analyzes, and translates complex business questions into analytical projects and AI-powered capabilities. Manages and delivers critical AI/ML projects and discovers and verifies new opportunities to identify risk, grow business, scale and optimize operations. Works across technology, data science and business functions to develop solutions at all levels of the organization.
Primary Responsibilities:
Provides AI/ML leadership on analytic projects, often across one or more units and functions.
Works directly with technology teams to integrate data science models into production systems.
Develops and delivers reports on findings for technical and non-technical audiences.
Provides core reviews for algorithm designs and implementations.
Develops and applies mathematical or statistical theory and methods to collect, organize, and analyze data.
Develops decision support software, services, and products.
Formulates mathematical and simulation models of problems, relating constants and model features, as well as their restrictions and alternatives.
Performs validation and tests of models to ensure adequacy and reformulate models as necessary.
Defines and validates data and integration requirements for model pipelines.
Analyzes, manipulates, and processes large sets of data using statistical and machine learning software.
Identifies business problems or management objectives that can be addressed through AI or other similar predictive model and data analysis.
Recommends AI and data-driven solutions to key stakeholders.
Establishes and project manages analysis plans for multiple complex work streams.
Education and Experience:
Bachelor's degree in Computer Science, Data Science, Engineering, Engineering Management, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and five (5) years of experience as a Senior Manager, Data Science (or related occupation) researching and building scalable Artificial Intelligence (AI) solutions using Machine Learning (ML) and Natural Language Processing (NLP) models and technologies to improve customer experience and drive business results.
Or, alternatively, Master's degree in Computer Science, Data Science, Engineering, Engineering Management, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and three (3) years of experience as a Senior Manager, Data Science (or related occupation) researching and building scalable Artificial Intelligence (AI) solutions using Machine Learning (ML) and Natural Language Processing (NLP) models and technologies to improve customer experience and drive business results.
Skills and Knowledge:
Candidate must also possess:
Demonstrated Expertise (“DE”) performing advanced statistical analysis to develop and evaluate supervised and unsupervised ML algorithms -- Regression, Decision Trees, Neural Networks, Feature Selection, Hyper-Parameter tuning, and ranking models -- using Python and ML libraries (scikit-learn, Tensorflow, Keras, or PyTorch).
DE designing and developing NLP solutions to process unstructured and semi-structured text for NLP tasks - Named Entity Extraction (NER), intent detection, classification, or clustering --using classical NLP and ML methods (Deep Learning (DL) and embeddings).
DE refactoring production-level code to achieve greater run-time performance and low latency; prototyping and deploying ML solutions using Docker-containers and Cloud-based environments (Amazon Web Services (AWS) servers or AWS SageMaker); and building service end-points, using REST API and Flask.
DE developing and implementing multimodal recommendation engines, content generation to drive web click-rates using advanced AI/ML libraries and algorithms -- Multi-Arm Bandits, Champion-Challenger, and user-based similarity models.
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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.
Top Skills
What We Do
At Fidelity, our goal is to make financial expertise broadly accessible and effective in helping people live the lives they want. We do this by focusing on a diverse set of customers: - from 23 million people investing their life savings, to 20,000 businesses managing their employee benefits to 10,000 advisors needing innovative technology to invest their clients’ money. We offer investment management, retirement planning, portfolio guidance, brokerage, and many other financial products.
Privately held for nearly 70 years, we’ve always believed by providing investors with access to the information and expertise, we can help them achieve better results. That’s been our approach- innovative yet personal, compassionate yet responsible, grounded by a tireless work ethic—it is the heart of the Fidelity way.
