Senior Machine Learning Engineer, Causal & Decision Systems

🕒 August 15

🤠 Texas – Remote

🤠 Texas – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 23%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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CSC Generation

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

🛒 Retail

🛍️ eCommerce

🤖 Artificial Intelligence

💰 Venture Round on 2019-01

Retail • eCommerce • Artificial Intelligence

CSC Generation is a retail technology platform that enhances revenue growth and unit margin management through automation and AI. The company manages a diverse portfolio of 325,000 products online and receives over 10 million monthly page views across its brands. CSC Generation specializes in retail, ecommerce, and wholesale, with a commitment to expanding by acquiring successful brands. Founded in 2016 by Justin Yoshimura, CSC Generation has acquired several well-known brands including One Kings Lane and Sur La Table, and continues to seek out new brands to join its network. The company offers extensive career opportunities and focuses on creating an inspiring and challenging work environment.

📋 Description

• Build closed-loop decision systems using machine learning for pricing and other consumer-business decisions • Estimate causal responses and quantify uncertainty • Choose actions, generate useful information, observe outcomes, and update policies • Evaluate challenger policies and deploy systems within guardrails • Work across causal and heterogeneous treatment-effect modeling, uncertainty estimation, contextual bandits, active learning, sequential decision-making, policy learning, constrained optimization, counterfactual evaluation, experimentation, production ML infrastructure, monitoring, and automated deployment • Produce measurable economic lift in controlled experiments • Generalize systems across businesses and safely automate commercial decisions • Apply the decision-system capability across a portfolio of businesses and increasingly broad commercial decisions

🎯 Requirements

• Exceptional technical ability and judgment • Experience in several of machine learning and statistical modeling, causal inference and experimentation, recommendation, advertising, pricing, marketplace, credit, or other decision systems • Experience with bandits, reinforcement learning, optimization, active learning, uncertainty estimation, counterfactual evaluation, or production ML systems • Python and SQL proficiency • Experience working with large behavioral datasets