(usa) Senior Manager, Data Science (ai Technical Lead) – Next-gen Customer Engagement & Returns

What you'd actually do

1. Architect Autonomous AI Systems: Design the end-to-end algorithmic framework for our proactive returns intelligence agent. You will fuse Causal Inference, Deep Learning, and Large Language Models (LLMs) to analyze structured transaction data alongside unstructured customer feedback, chat logs, and product reviews.
2. Lead the Transition from Insight to Action: Spearhead the application of Causal AI to understand the _"why"_ behind return behaviors. You will move the team beyond simple correlation to answer counterfactuals (e.g., _"If we offer a 15% discount right now, will it save the sale and the customer relationship?"_).
3. Drive Engineering Excellence: Act as the ultimate gatekeeper for the AI codebase. You will mentor a team of brilliant Data Scientists, elevating their engineering maturity from local "notebook scripts" to scalable, modular, and deployable production packages. You will enforce strict version control (Git), conduct rigorous code reviews, and mandate comprehensive unit/integration testing.
4. Pioneer ML & GenAI Observability: The real world is chaotic. You will design state-of-the-art MLOps and monitoring frameworks to track real-time model performance, data drift, and LLM hallucination rates. You ensure our AI agents adapt dynamically as consumer trends and macroeconomic factors shift.
5. Strategic Technical Leadership: Translate highly ambiguous business objectives ("Reduce omni-channel friction") into concrete, executable AI roadmaps. You will bridge the gap between complex algorithmic concepts and executive business strategy.

Skills

What the JD emphasized

• Architect Autonomous AI Systems
• Causal Inference
• Deep Learning
• Large Language Models (LLMs)
• Causal AI
• Engineering Excellence
• MLOps
• monitoring frameworks
• Python
• PySpark

Other signals

• Agentic AI
• Causal Machine Learning
• LLMs
• MLOps
• Observability