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Talent Sourcer – Machine Learning & Quantitative Research

As an ML and Quantitative Research Sourcer, you will be focused on identifying and engaging experienced talent across Machine Learning and Quantitative Research, mapping competitiv

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IMC Chicago Source published Sep 20, 2026 Verified 11 hours ago
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EmploymentFull-time

Overview

As an ML and Quantitative Research Sourcer, you will be focused on identifying and engaging experienced talent across Machine Learning and Quantitative Research, mapping competitiv

Full job description

As an ML and Quantitative Research Sourcer, you will be focused on identifying and engaging experienced talent across Machine Learning and Quantitative Research, mapping competitive talent landscapes, building relationships with high-caliber technical professionals, and developing creative sourcing strategies that strengthen IMC’s presence within the broader ML and quantitative communities. You will partner closely with recruiters and hiring managers to deliver strong pipelines of experienced candidates, assess talent against our technical and cultural standards, and provide market insights that inform hiring strategy. Your Core 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 Skills & Experience 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 Please note that immigration sponsorship is not offered for this specific opening. The Base Salary range for the role is included below. Base salary is only one component of total compensation; all full-time, permanent positions are eligible for a discretionary bonus and benefits, including paid leave and insurance. Please visit Benefits - US | IMC Trading for more comprehensive information. Salary Range $100,000 — $150,000 USD About Us IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.  

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