Principal AI Data Scientist

ZipRecruiter - Phoenix, AZ

Full-time - Principal

Remote - Phoenix, AZ

About the position

The Principal AI Data Scientist will lead AI initiatives involving computer vision, deep learning, and natural language processing (NLP) for a large retailer. This role focuses on solving complex problems and enhancing the company's internal research and development capabilities to maintain a competitive edge in the analytics industry. The position involves working on large-scale projects that deliver value to customers and collaborating with various teams to drive business outcomes.

Responsibilities

• Builds and validates machine learning models for high risk/reward problems using large scale data from multiple sources.
• Creates data-driven solutions for various business use-cases using machine learning techniques.
• Writes programs utilizing existing libraries and methodologies.
• Interprets, communicates, and presents analytic results to C-Level executives and below.
• Collaborates with fellow data scientists, data engineers, business partners, project managers, and key stakeholders to drive business value.
• Leads AI best practice sharing and stays updated on industry trends and innovations in data science.
• Manages projects with external partners and vendors to develop solutions that meet business needs.
• Contributes to the organization's data strategy and roadmap.
• Embeds and drives the organization with the latest AI methodologies.

Requirements

• Master's or PhD degree in a quantitative field.
• 5+ years of data science experience.
• Applied expertise in artificial intelligence, particularly in natural language processing and computer vision.
• Proficiency in machine learning techniques, including decision trees, gradient boosting, and XGBoost.
• Programming expertise in Python and familiarity with cloud environments such as AWS and Databricks.
• Ability to work with large datasets from multiple sources.
• Strong communication skills to convey complex analytics concepts to C-Level executives and other stakeholders.
• Collaborative mindset to work with data scientists, data engineers, and external partners.
• Intellectual curiosity and a passion for data.