Data Scientist - eCommerce

Responsibilities

• Buils a framework to stitch cross domains learning; optimizes them toward mission-specific and multi-mission tasks
• Serves as expert specializing in AI interpretation and causality; uncovers ML model's causality relationships; builds framework to measure each model's bias, underspecification, and latent drivers with their connections
• Creates an enterprise domain-specific reasoning system to boost actionable insights and optimize the resources of machine learning process
• Orchestrates reusable storytelling methodology to apply toward AI translation
• Applies an inquisitive nature to creating ML / AI transparency to the business
• Applies AI reasoning into business action recommendations
• Applies AI research to accelerate business innovation

Requirements

• A related degree or comparable formal training, certification, or work experience
• 7+ years of experience in a retail or retail-related decision science role
• Experience translating data science findings into business-friendly results
• Experience presenting findings to leaders and peers
• Ability to contribute to multiple work streams concurrently
• Experience with Clickstream Analytics (BQ/Amplitude)
• Capable of working with visualization tools such as Tableau and Dash, flask, d3, bokeh, streamlit, plotly
• Ability to create end-to-end ML solutions with guidance
• Able to adapt within the team’s foundational design (Confluence, Jira, Git, IDE’s)
• Open to learning new methodologies and application of ML techniques
• Expertise in ML visualization flow
• Expertise in optimizing distributed machine learning in a heterogeneous domain environment
• Technical knowledge in programming languages: SQL, R, Python, Scala, Java, C/C++
• Technical knowledge in big data / ML optimization: GPU code optimization, Horovod, Spark MLlib optimization, Cython, JNI, Numba
• Technical knowledge in mainstream ML / AI: manifold learning, distributed clustering, graph network, hierarchical model, Bayesian network, deep learning, computer vision, NLP/NLU, reinforcement learning, meta-Learning, federated learning
• Skills to consider and apply causal reasoning representation and learning, and human-centric, explainable, responsible AI
• Ability as a creative storyteller and translator between business questions and ML solutions
• Ability to work comfortably with imperfect or incomplete data
• Ability to apply AI reasoning into business action recommendations

Qualifications

• Work in a fast-paced retail environment with frequently shifting priorities
• Sit for long periods
• Work extended hours