Director, GenAI Technology

About the role

This is an individual contributor applied GenAI engineer/data science (with a focus on GenAI) role. The GenAI Technology team within Fidelity's Asset Management Technology is looking for a motivated applied GenAI engineer/data scientist with proven experience in machine learning, GenAI-related projects, application building and data science.

Responsibilities

• Leads machine learning projects with diverse scope and complex business and technical challenges.
• Collaborates with senior business and technology partners to develop solutions to the most complex business analytical needs.
• Oversees end-to-end process to push code from research to production.
• Delivers results with clear and measurable impact to the business.
• Consults with senior business and technology partners to identify priorities and establish analytic goals.
• Executes on direction for data identification, collection and qualification activities.
• Presents reports and findings to senior technical and non-technical audiences.
• Works on and drives progress for multiple projects at the same time.
• Guides business on identifying AI/ML use cases and optimally contributing to brainstorming sessions.

Requirements

• PhD or Master's in Data Science, Computer Science, Statistics, Physics, or Finance (with a background in Statistics), with 4 years plus of industrial experience.
• Experience working with LLMs for solving data science problems, information retrieval applications, clustering, and coding Deep expertise in Python, as well as data-centric techniques including engineering principles for building efficient inference tools.
• Experience taking an application from research to production and realizing measurable value from it to the team or firm.
• Ability to work on and drive progress for multiple projects at the same time.
• Desires to create a climate that values and rewards contributions, drive, ownership, initiative, and achievement of results.
• Excellent planning, project management, leadership, and research skills.
• Experience communicating results to business stakeholders with a focus on clear, concise, and understandable delivery including conveying statistical findings through data visualizations.
• Enthusiasm for learning new skills and domains, including applying state-of-the-art ML research and LLMs to real-world data challenges.

Qualifications

• You Will Have PhD or Master's in Data Science, Computer Science, Statistics, Physics, or Finance (with a background in Statistics), with 4 years plus of industrial experience.

Skills

• Deep expertise in Python, as well as data-centric techniques including engineering principles for building efficient inference tools.
• Experience taking an application from research to production and realizing measurable value from it to the team or firm.
• Excellent planning, project management, leadership, and research skills.
• Experience communicating results to business stakeholders with a focus on clear, concise, and understandable delivery including conveying statistical findings through data visualizations.
• Enthusiasm for learning new skills and domains, including applying state-of-the-art ML research and LLMs to real-world data challenges.

Benefits

• We offer a wide range of benefits to meet your evolving needs and help you live your best life at work and at home. These benefits include comprehensive health care coverage and emotional well-being support, market-leading retirement, generous paid time off and parental leave, charitable giving employee match program, and educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career.

Pay

The base salary range for this position is $126,000-255,000 USD per year. Placement in the range will vary based on job responsibilities and scope, geographic location, candidate’s relevant experience, and other factors. Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.

Schedule

Fidelity’s Onsite Working Model: Fidelity is transitioning to a full-time onsite working model through a phased rollout across regions and roles. Currently, some roles and locations require 100% onsite presence, while others require less. Onsite expectations are likely to evolve as the rollout continues. This transition does not apply to fully remote roles.