Senior ML Engineer for Causal Decision Systems

Cscgeneration 2; Austin (TX); On-site; USD 150,000 - 210,000; Full time

Job summary

CSC Generation is building closed-loop decision systems that use machine learning to operate consumer businesses more intelligently. We are starting with pricing and expanding into inventory, purchasing, promotions, marketing, and assortment.

As a Senior ML Engineer you will architect models that estimate causal effect, quantify uncertainty, and guide actions while observing outcomes and updating policies. You will deploy within guardrails and scale across a portfolio of businesses.

Qualifications

• Experience in machine learning and statistical modeling.
• Experience in causal inference and experimentation.
• Experience with decision systems in pricing, marketplace, or related domains.
• Knowledge of bandits, reinforcement learning, optimization, or active learning.
• Experience with uncertainty estimation and counterfactual evaluation.
• Proficiency in Python, SQL, and handling large behavioral datasets.

Responsibilities

• Build causal and heterogeneous treatment-effect models.
• Develop uncertainty estimation and calibration methods.
• Develop contextual bandits, active learning, or sequential decision-making.
• Work on policy learning and constrained optimization.
• Perform counterfactual and off-policy evaluation.
• Support experimentation and champion/challenger systems.
• Contribute to production ML infrastructure, monitoring, and automated deployment.

Skills

Machine learning

Statistical modeling

Causal inference

Experimentation

Uncertainty estimation

Python

SQL

Large datasets

Job description

CSC Generation is building closed-loop decision systems that use machine learning to operate consumer businesses more intelligently. We are starting with pricing and expanding into inventory, purchasing, promotions, marketing, and assortment.

As a Senior ML Engineer you will architect models that estimate causal effect, quantify uncertainty, and guide actions while observing outcomes and updating policies. You will deploy within guardrails and scale across a portfolio of businesses.