Job Description:

Position Description:

Performs large-scale data preprocessing, manipulation, and analytical tasks. Develops supervised and un-supervised Machine Learning (ML) algorithms (regression, decision trees/random forest, and neural networks). Designs and implements Natural Language Processing (NLP) solutions, including the use of Large Language Models (LLMs) and generative Artificial Intelligence (AI), to enhance text understanding and generation capabilities. Researches and builds sophisticated, innovative, and scalable AI algorithms, models, and platforms to improve customer experience and drive business outcomes. Leads initiatives involving extensive multi-dimensional databases, complex business infrastructure, and collaboration with cross-functional teams.

Primary Responsibilities:

• Identifies business opportunities and evaluates best approaches for predictive or prescriptive analytics.
• Gathers internal and external data (structured or unstructured) from multiple sources using any programming languages necessary with minimal senior support.
• Implements best practices for model development, iteration, as well as code management and conducts code reviews.
• Draws key business insights from advanced quantitative analyses and presents findings to broader audience and senior management.
• Supports junior team members in learning data sources, tools, and technologies.
• Develops and implements a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software.
• Applies data mining, data modeling, natural language processing, and machine learning for extracting and analyzing information from large structured and unstructured datasets.
• Visualizes, interprets and reports data findings.

Education and Experience:

Bachelor’s degree (or foreign education equivalent) in Computer Science, Economics, Engineering, Information Technology, Information Systems, Mathematics, Data Science, Computational Finance, or a closely related field and six (6) years of experience as a Director, Data Science (or closely related occupation) performing data analytics, building statistical models, and developing business intelligence applications to improve customer experience and drive business results in a financial services environment.

Or, alternatively, Master’s degree (or foreign education equivalent) in Computer Science, Economics, Engineering, Information Technology, Information Systems, Mathematics, Data Science, Computational Finance, or a closely related field and four (4) years of experience as a Director, Data Science (or closely related occupation) performing data analytics, building statistical models, and developing business intelligence applications to improve customer experience and drive business results in a financial services environment.

Skills and Knowledge:

Candidate must also possess:

• Demonstrated Expertise (“DE”) performing large-scale data extraction, transformation, and loading processes in large data warehouses with SQL, Apache Hive, or Python; and integrating and managing data across databases and platforms (SQL Server, Oracle, or AWS S3).
• DE designing and building Machine Learning (ML) models (regression, classification, decision trees, clustering, and recommender systems) and Deep Learning (DL) models (LSTM, VAE, and Transformers) in Python using Scikit-Learn, Transformers, or PyTorch; and performing distributed model training and hyperparameter optimization using Amazon Web Services (AWS) SageMaker.
• DE validating/assessing model soundness and performance by conducting in-sample and out-of-sample testing using RMSE, R-squared, AUC ROC, Precision, or Recall; and documenting model assumptions, methodologies, limitations, and usage guideline to ensure adherence to model governance and model risk management policies.
• DE designing and implementing Natural Language Processing (NLP) solutions to enhance the efficiency of financial document processing and automation, utilizing Large Language Models (LLMs) and generative AI technologies; applying Retrieval-Augmented Generation (RAG) methods to improve information retrieval and extraction using Python with LangChain, LangGraph, and Transformers.

Salary: $192,000.00 - $212,000.00/year.

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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.