Principal Applied Scientist (Shopping)
Core
Discover insights from massive datasets to resolve customer pain points and develop/deploy ML, deep learning, and LLM-based solutions for commerce intelligence and user profiling.
Role type
Principal Applied Scientist (Shopping)
Builds
Scalable production systems for conversion understanding, user profiling, identity linking, and commerce intelligence.
Domain
E-commerce / Machine Learning / Large-scale Data
Deliverable
production ML models
Required skills
Machine learning, Deep learning, LLMs, Python, Big data modeling, Agentic engineering, RAG, Fine-tuning, Context engineering, A/B testing design, Experimentation, Data visualization, Metrics design
Preferred skills
NLP, Recommender systems, User behavior modeling, Cloud platforms (Azure, AWS, GCP), SQL/NoSQL, ML frameworks (TensorFlow, PyTorch, Keras)
Technologies
Python, Spark, Azure, AWS, Google, PowerBI, Tableau, SQL, NoSQL, TensorFlow, Keras, PyTorch, Caffe
Responsibilities
Own data science projects end-to-end from problem definition to model evaluation; Prototype and evaluate creative ideas; Partner with engineering/product to translate innovations to production; Design metrics and A/B testing frameworks; Drive data-driven decision making through rigorous evaluation.
Seniority
Principal, hands-on IC with strategy & mentorship
