Job Description:

Position Description:

Consults with business and technology partners to identify priorities and establish data analytic goals. Translates use cases to Artificial Intelligence (AI), Machine Learning (ML), and analytics -- data, algorithms and validation strategy. Drives data identification, collection, and qualification activities. Leads efforts to identify signals in data that address use cases directly or can be leveraged by analytics teams. Designs and provides critical reviews for algorithmic approaches.

Primary Responsibilities:

• Provides ML leadership on complex projects, often across several business units and functions.

• Works directly with technology teams to integrate data science models into production systems.

• Writes and delivers reports on findings for technical and non-technical audiences. Provides critical reviews for algorithm designs.

• Provides core reviews for algorithm implementations.

• Conducts research and publications for the technical community.

• Assesses data and algorithm design recommendations from data scientists and recommends changes to larger and more complex systems.

• Defines data and model governance practices to operationalize standards.

• Formulates mathematical and simulation models of problems, relating constants and variables, restrictions, alternatives, conflicting objectives, and their numerical parameters.

• Performs validation and testing of models to ensure adequacy and reformulate models.

• Manages the formulation of mathematical modeling and optimizing methods to develop and interpret information that assists management with decision making, policy formulation, or other managerial functions.

• Collects and analyzes data and develops decision support software, service, or products.

• Develops and supplies optimal time, cost, or logistics networks for program evaluation, review, or implementation.

• Elicits, captures, and interprets customer problems from multiple perspectives across projects or within a program.

• Establishes and project manages analysis plans for multiple complex work steams.

• Manages the estimation, planning, analysis, design, and development of projects.

• Holds accountability for integration into larger, multi-disciplined projects, as appropriate.

• Leads and oversees ML strategy and road map planning.

• Works across teams to influence and lead the direction of external teams.

Education and Experience:

Bachelor’s degree (or foreign education equivalent) in Analytics, Data Science, Advanced Computer Science, Computer Science, Engineering, Information Technology, Information Systems, Mathematics, or a closely related field and five (5) years of experience as a Senior Manager, Data Science (or related occupation) researching and building scalable AI solutions using ML and Natural Language Processing (NLP) models and technologies to improve customer experience and drive business results.

Or, alternatively, Master’s degree (or foreign education equivalent) in Analytics, Data Science, Advanced Computer Science, Computer Science, Engineering, Information Technology, Information Systems, Mathematics, or a closely related field and two (2) years of experience as a Senior Manager, Data Science (or related occupation) researching and building scalable AI solutions using ML and Natural Language Processing (NLP) models and technologies to improve customer experience and drive business results.

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

Skills and Knowledge:

Candidate must also possess:

• Demonstrated Expertise (“DE”) performing advanced statistical analytics 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); and launching ML and DL models in a production environment and performing data and runtime profiling of the solutions to assess the efficacy of the ML and AI algorithms.

• DE processing and analyzing large scale datasets and reviewing for AI biases using time series analysis, econometrics, and statistical inferences.

• 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.

[Expertise may be gained during doctoral program].

Salary: $156,375.00-$162,200.00/year.

#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.