Job Description:

The Role

This is an individual contributor data science role. In this role, the individual leads machine learning projects with diverse scope and complex business and technical challenges. Coordinates 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. Enjoys collaboration and revels in working as part of a team to solve deep applied problems.

You will have:

PhD or Master's in AI/ML, Computer Science, Statistics, Physics or Finance (with a background in Machine learning), with 6+ years plus of industrial experience.
Deep expertise in Python, data-centric AI/ML techniques
Experience taking a model 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
Experience guiding business on identifying AI use cases and optimally contributing to brainstorming sessions
Desires to create a climate that values and rewards contributions, drive, ownership, initiative, and achievement of results
Excellent planning, project management, consulting, leadership, and talent management skills
Experience communicating results to business stakeholders with a focus on clear, concise, and understandable delivery

The Team

We are a data science team within the Quantitative Research and Investment Technology division in the Asset Management vertical. We partner with investment professionals, portfolio managers, analysts, quants, traders, and other technology teams to build AI/ML solutions that provide insight and drive measurable value. We focus on applied problems that can be taken from research to production. We enjoy learning new skills and have incorporated some LLM use cases into our pipeline, amongst other emerging technologies.

Certifications:

Category:

Data Analytics and Insights

Fidelity's hybrid working model blends the best of both onsite and offsite work experiences. Working onsite is important for our business strategy and our culture. We also value the benefits that working offsite offers associates. Most hybrid roles require associates to work onsite every other week (all business days, M-F) in a Fidelity office.