Lead GenAI projects with diverse scope and complex business and technical challenges
Coordinate with senior business and technology partners to develop solutions to the most complex business analytical needs
Oversee end-to-end process to push code from research to production
Deliver results with clear and measurable impact to the business
Consult with senior business and technology partners to identify priorities and establish analytic goals, as well as form alignment on next steps
Execute on direction for data identification, collection and qualification activities
Present reports and findings to senior technical and non-technical audiences
Enjoy collaboration and revels in working as part of a team to solve deep applied problems
Execute on multiple initiatives in parallel
Play an active mentorship role to others in the team
Requirements
PhD or Master's in Data Science, Computer Science, Statistics, Physics, or Finance (with a background in Statistics), with 7 plus years of industrial experience
Experience working with LLMs for solving data science problems, information retrieval applications, clustering, and coding
Experience working and closely collaborating with an Engineering team, sharing best development practices under a common goal of shipping reliable software
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 or initiatives at the same time
Experience guiding business on identifying AI/ML use cases and optimally contributing to brainstorming sessions or consulting sessions
Desires to create a climate that values and rewards contributions, drive, ownership, initiative, and achievement of results
Excellent planning, project management, communication, 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