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AI-First Data Scientist

2 hours, 16 minutes ago
United States
Full-time
Senior
Data Scientist
Data Science and Analytics
AWS CI/CD Feature Engineering Generative AI Git Jupyter Machine Learning MLOps Python R Reinforcement Learning SageMaker SQL
Apply Now
CSC Generation

CSC Generation

CSC Generation is an AI native retail holding entity that revitalizes iconic brands through the use of data, automation, and its Genesis platform to shape the future of commerce in the age of artificial general intelligence.

Internet Software & Services
251-1K
Founded 2016
View All Jobs 12

Description

  • Develop and deploy end-to-end machine learning pipelines using modern MLOps practices and cloud-native infrastructure.
  • Conduct causal analysis and treatment effect estimation using DML, causal forests, uplift modeling, and related counterfactual methods.
  • Build, train, and optimize predictive and prescriptive models for pricing, promotions, inventory, marketing attribution, and personalization.
  • Integrate models into production systems and monitor performance, drift, and data quality issues using observability tools.
  • Translate ambiguous business problems into machine learning frameworks that deliver measurable ROI.
  • Partner with engineering teams to improve data pipelines, reproducibility, and version-controlled CI/CD-enabled ML workflows.
  • Research and apply emerging AI techniques, including generative AI, automated feature engineering, and reinforcement learning.
  • Take complex problems end to end from exploration and feature design through model selection, backtesting, deployment, and impact measurement.
  • Design A/B tests, holdouts, staggered rollouts, and other quasi-experiment setups when randomized testing is not feasible.

Requirements

  • 5+ years of experience in applied data science or machine learning engineering, with a proven track record of deploying ML models into production.
  • Master's or PhD degree in Data Science, Computer Science, Statistics, Economics, or a 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 is 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

  • Competitive compensation.
  • Executive access to brand CEOs and senior leadership with direct mentorship opportunities.
  • Hands-on experience with advanced AI tools and modern automation workflows.
  • Accelerated career growth with opportunities for greater responsibility and leadership across the portfolio.
  • Paid time off policies.
  • 401(k)/RRSP match.
  • Medical, dental, and vision coverage plus supplemental insurance options.
  • Employee discounts at portfolio companies.

Interested in this position?

Apply directly on the company website

Apply Now

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