Talent Sourcer – Machine Learning & Quantitative Research

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

$100K-$150K not verified - source not recorded; timestamp not recorded

401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

12% above the BLS role benchmark for data and ml aggregate.

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Talent Sourcer – Machine Learning & Quantitative Research Chicago, United States 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,

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