Talent Sourcer - Machine Learning & Quantitative Research
Required skills
Bachelor's Degree; 4-7 years of sourcing experience focused on technical hiring, ideally within Machine Learning, Quantitative Research, or related technical domains, Strong understanding of ML, AI, quantitative research, and broader technical talent landscapes, Demonstrated success building relationships with and engaging experienced technical talent in competitive markets, Experience identifying and engaging talent through channels such as GitHub, Kaggle, Hugging Face, LinkedIn Recruiter, research publications, and other technical communities, Proven ability to develop and execute sourcing strategies using data, feedback, and market insights, Collaborative approach with experience partnering closely with recruiters and hiring managers in fast-paced environments, Strong communication, organizational, and stakeholder management skills, with the ability to manage multiple searches simultaneously and operate with a high degree of ownership
Responsibilities
Partner with recruiters and hiring managers to understand hiring needs across Machine Learning and Quantitative Research functions, Develop and execute creative sourcing strategies to identify and engage experienced talent, Build and maintain strong pipelines of passive candidates across key technical markets, Conduct market mapping and talent landscape analysis to support hiring strategy and workforce planning, Leverage LinkedIn Recruiter, GitHub, Kaggle, research publications/conferences, referrals, and other creative sourcing channels to identify and engage top technical talent, Engage candidates with compelling outreach and ensure a positive candidate experience throughout the sourcing process, Track sourcing activity, pipeline health, and market insights to inform recruiting decisions, Collaborate closely with recruiting teams to continuously improve sourcing processes and effectiveness
Domain
Machine Learning, Quantitative Research
