AI-First Data Scientist

🕒 December 13, 2025

🌵 Arizona, Florida, +15 more states – Remote

🌵 Arizona – Remote 🐊 Florida – Remote ⚜️ Louisiana – Remote 🎰 Nevada – Remote 🌲 North Carolina – Remote 🌪️ Oklahoma – Remote 🚗 Michigan – Remote 🎸 Mississippi – Remote 🏰 Missouri – Remote 🔔 Pennsylvania – Remote 🎸 Tennessee – Remote 🤠 Texas – Remote ⛷️ Utah – Remote ⚔️ Virginia – Remote ⛰️ West Virginia – Remote 🧀 Wisconsin – Remote 🦬 Wyoming – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

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CSC Generation

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

🛒 Retail

🛍️ eCommerce

💰 Venture Round on 2019-01

Retail • eCommerce • AI

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

• Develop and deploy end-to-end ML pipelines using modern MLOps practices, cloud-native platforms (e.g., AWS Sagemaker), and scalable infrastructure. • Conduct causal analysis and treatment effect estimation using DML, causal forests, uplift modeling, and other counterfactual inference techniques to guide high-stakes business strategy. • Build, train, and optimize predictive and prescriptive models for use cases like pricing, promotions, inventory, marketing attribution, and personalization. • Integrate models into production systems and monitor their performance using advanced observability tools (yes, even Happyface), including diagnosing drift and data quality issues. • Partner directly with business leaders to translate ambiguous business problems into machine learning frameworks that deliver measurable ROI. • Collaborate with engineering teams to improve data pipelines, ensure model reproducibility, and maintain version-controlled, CI/CD-enabled ML workflows. • Continuously research and apply emerging techniques in AI, including generative AI, automated feature engineering, and reinforcement learning. • Take complex, high-impact problems end to end - from exploration and feature design through model selection, backtesting, and production deployment with clear impact metrics. • Design robust experiment and quasi-experiment setups (A/B tests, holdouts, staggered rollouts) and recommend approaches when fully randomized tests are not feasible.

🎯 Requirements

• 5+ years of experience in applied data science, machine learning engineering, with a proven track record of deploying ML models into production. • Master or PhD degree in Data Science, Computer Science, Statistics, Economics, or related quantitative field. • Expertise in causal inference frameworks—especially Double Machine Learning (DML), A/B testing, uplift modeling, and other counterfactual methods. • Strong proficiency in Python or R, with hands-on experience in SQL, Jupyter, Git, and cloud ML platforms (AWS Sagemaker experience preferred). • Familiarity with MLOps tools for experiment tracking, model registry, reproducibility, and automated deployment. • Experience working with large datasets, distributed computing frameworks, and data engineering best practices. • Strong experience applying advanced causal and time-series methods in real-world settings, including diagnosing bias, drift, and data quality issues. • Demonstrated ability to independently take ambiguous, cross-functional problems from zero to a deployed ML solution with clear success metrics and post-launch evaluation.

🏖️ Benefits

• Executive Access: Work directly with brand CEOs and senior leadership, solving real business problems and earning mentorship from top operators. • AI-First Skill Building: Get hands-on with the most advanced AI tools in the market. From automation to prompt engineering, you’ll build a modern tech stack that sets you apart in any industry. • Accelerated Career Path: High performers are quickly entrusted with greater responsibility, new challenges, and leadership opportunities across our portfolio of brands. • Competitive Benefits: Paid time off policies, 401(k)/RRSP match, medical/dental/vision and a variety of supplemental policies, and employee discounts at our portfolio companies.