Senior Data Scientist, Supply Chain Optimization

What you'll do

• Design and deploy intelligent agents to optimize fulfillment routing and supply chain workflows.
• Build agents capable of reasoning, planning, and tool usage using LangChain, LangGraph, and Pydantic.
• Implement trainable model architectures and NLP solutions using PyTorch, TensorFlow, and HuggingFace.
• Develop scalable Retrieval-Augmented Generation (RAG) systems using vector databases and knowledge graphs.
• Apply machine learning techniques like XGBoost and K-Means to large-scale structured and unstructured datasets.
• Deploy AI/ML systems into production using Docker, Kubernetes, and CI/CD pipelines.
• Develop evaluation and observability frameworks to monitor model performance, hallucination rates, and latency.
• Translate AI research from conferences like NeurIPS and ICML into scalable enterprise solutions.

What we're looking for

• Bachelor’s degree in Computer Science, Analytics, Engineering, or a related field plus 1 year of experience in analytics.
• Master’s degree or the equivalent in Computer Science, Analytics, Engineering, or a related field.
• Experience building Deep Learning model architectures in Python using PyTorch, TensorFlow, and LangChain.
• Experience pre-training and fine-tuning language models from HuggingFace or TFHub for NLP tasks.
• Experience with generative models (GPT) and encoder-based models (BERT, RoBERTa) for language-based reasoning.
• Proficiency in advanced statistical and modeling methods using scikit-learn, scipy, and computational semantics tools like SpaCy or NLTK.
• Experience with CI/CD, testing, and documentation in software development using UML, State and Activity workflows, and Java.
• Experience with Docker, Kubernetes, cloud platforms (GCP/Azure), Airflow, and vector databases (Pinecone, Milvus, ChromaDB).