Job Description:

Position Description:

Develops and deploys Machine Learning (ML) enabled products and services at scale using Deep Learning (DL) methodologies related to document automation, computer vision, and natural language models. Solves business problems — Business to Consumer (B2C), Business to Business (B2B), quality operations, operations management, and automation — using Artificial Intelligence (AI) and data science techniques (Natural Language Processing (NLP), DL, ML, causal inference, predictive analytics, experimental design, and optimization). Leads a team of data scientists, collaborates closely with data engineers, system integration engineers, quality engineers, and business stakeholders to solve challenges, text analytics problems, with innovative solutions. Owns the delivery of AI-enabled applications. Provides analytic consults to the business and identifies and gathers complex data from multiple sources. Conducts experiments to test algorithms, monitor model performance, interpret findings, and present work to technical and non-technical audiences.

Primary Responsibilities:

• Performs applied research in ML, computer vision, recommender systems, NLP, time series models, transformers, graphs and their applications in search, and personalization and marketing.

• Leads and manages high performance data science teams and delivers industry leading AI-enabled products and services.

• Leads and implements document processes, computer vision, and DL.

• Leads and deploys projects involving large scale multi-dimensional databases, complex business infrastructure, and cross-functional teams.

• Leads the design and development of innovative solutions for customer and associate-centric projects -- text mining, document/image processing, and document-processing workflows.

• Implements new technologies in production environments.

• Guides data science and engineering teams to deliver projects and capabilities at scale.

• 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 and modeling, NLP, and ML techniques to extract and analyze information from large structured and unstructured datasets.

• Visualizes, interprets, and reports data findings.

Education and Experience:

Bachelor’s degree (or foreign education equivalent) in Applied Mathematics, Computer Science, Engineering, Information Technology, Information Systems, Information Management, Mathematics, or a closely related field and five (5) years of experience as a Director, Data Science (or closely related occupation) launching, operating, leading and implementing document processing, computer vision, and Deep Learning (DL) practices using TensorFlow, Keras, MXNET, or H2O.

Or, alternatively, Master’s degree (or foreign education equivalent) in Applied Mathematics, Computer Science, Engineering, Information Technology, Information Systems, Information Management, Mathematics, or a closely related field and two (2) years of experience as a Director, Data Science (or closely related occupation) launching, operating, leading and implementing document processing, computer vision, and Deep Learning (DL) practices using TensorFlow, Keras, MXNET, or H2O.

Or, alternatively, PhD in (or foreign education equivalent) in Applied Mathematics, Computer Science, Engineering, Information Technology, Information Systems, Information Management, Mathematics, or a closely related field and no experience.

Skills and Knowledge:

Candidate must also possess:

• Demonstrated Expertise (“DE”) developing semi-supervised, supervised, and unsupervised Machine Learning (ML) (in Python) and Deep Learning (DL) models (in PyTorch); applying functional paradigms -- Haskell -- to build composable learning systems and products; and performing probabilistic modeling, using PyStan, PyMC3, and Pyro.

• DE researching, applying, and deploying state-of-the-art Natural Language Processing (NLP) methods, using Python and DL frameworks -- PyTorch; and performing model compilation and optimization using TorchScript and ONNX.

• DE performing advanced statistical analytics to develop, analyze, and evaluate supervised and unsupervised ML algorithms -- Regression, Decision Trees/Random Forest, Neural Networks, Feature Selection/Reduction, Clustering, Hyper-Parameter tuning, marketing attribution models, and treatment control matching -- using Python, C , Java, Tensorflow, Keras, PyTorch, and Spark and scikit-learn -- with specific use cases on Recommender Systems and Reinforcement Learning/Bandits applications (within a planning, advice, and financial investments domain).

• DE contributing and designing enterprise architecture financial platforms, using highly available, scalable, fault tolerant, performance efficient, and resilient REST APIs and event based scalable frameworks using Amazon Web Services (AWS), Java/J2EE, NodeJs, Python, API Gateway, and Continuous Integration/Continuous Delivery (CI/CD) pipelines.

[Expertise may be gained during doctoral program].

#PE1M2

Certifications:

Company Overview

Fidelity Investments is a privately held company with a mission to strengthen the financial well-being of our clients. We help people invest and plan for their future. We assist companies and non-profit organizations in delivering benefits to their employees. And we provide institutions and independent advisors with investment and technology solutions to help invest their own clients’ money.

Join Us

At Fidelity, you’ll find endless opportunities to build a meaningful career that positively impacts peoples’ lives, including yours. You can take advantage of flexible benefits that support you through every stage of your career, empowering you to thrive at work and at home. Honored with a Glassdoor Employees’ Choice Award, we have been recognized by our employees as a top 10 Best Place to Work in 2024. And you don’t need a finance background to succeed at Fidelity—we offer a range of opportunities for learning so you can build the career you’ve always imagined.

Fidelity's working model blends the best of working offsite with maximizing time together in person to meet associate and business needs. Currently, most hybrid roles require associates to work onsite all business days of one assigned week per four-week period (beginning in September 2024, the requirement will be two full assigned weeks).

At Fidelity, we value honesty, integrity, and the safety of our associates and customers within a heavily regulated industry. Certain roles may require candidates to go through a preliminary credit check during the screening process. Candidates who are presented with a Fidelity offer will need to go through a background investigation, detailed in this document, and may be asked to provide additional documentation as requested. This investigation includes but is not limited to a criminal, civil litigations and regulatory review, employment, education, and credit review (role dependent). These investigations will account for 7 years or more of history, depending on the role. Where permitted by federal or state law, Fidelity will also conduct a pre-employment drug screen, which will review for the following substances: Amphetamines, THC (marijuana), cocaine, opiates, phencyclidine.

We invite you to Find Your Fidelity at fidelitycareers.com.

Fidelity Investments is an equal opportunity employer. We believe that the most effective way to attract, develop and retain a diverse workforce is to build an enduring culture of inclusion and belonging.

Fidelity will reasonably accommodate applicants with disabilities who need adjustments to participate in the application or interview process. To initiate a request for an accommodation, contact the HR Accommodation Team by sending an email to accommodations@fmr.com, or by calling 800-835-5099, prompt 2, option 3.