Senior Machine Learning Engineer - Causal Decision Systems

CSC Generation Enterprise; Austin (TX); On-site; USD 140,000 - 180,000; Full time

Job summary

CSC Generation Enterprise seeks a talented machine learning engineer to help build closed-loop decision systems across pricing, inventory, and promotions. You’ll design causal models, quantify uncertainty, and develop policies that drive measurable economic lift in controlled experiments.

We value strong technical judgment over checklists, with experience in Python, SQL, and large behavioral datasets, plus interest in production ML systems and experimentation.

Qualifications

• Experience building causal models and counterfactual evaluation.
• Proficient in Python and SQL and working with large datasets.
• Experience with bandits, reinforcement learning, and constrained optimization.
• Ability to reason about uncertainty in decision making.

Responsibilities

• Develop causal and heterogeneous treatment-effect models.
• Estimate uncertainty and calibrate models for policy decisions.
• Experiment with champion/challenger systems and production ML pipelines.
• Collaborate across pricing, inventory, and marketing domains.
• Deploy and monitor models within guardrails.

Skills

Machine learning

Causal inference

Reinforcement learning

Python

SQL

Experimentation

Production systems

Job description

CSC Generation Enterprise seeks a talented machine learning engineer to help build closed-loop decision systems across pricing, inventory, and promotions. You’ll design causal models, quantify uncertainty, and develop policies that drive measurable economic lift in controlled experiments.

We value strong technical judgment over checklists, with experience in Python, SQL, and large behavioral datasets, plus interest in production ML systems and experimentation.