Data Scientist: Enterprise Analytics

Introduction

This role encompasses designing and architecting analytical and predictive AI/ML systems, and overseeing their training, fine-tuning, and evaluation.

The ideal candidate will have 8+ years of experience building enterprise analytics platforms or business intelligence systems at scale and can design data infrastructure that consolidates diverse sources into unified, actionable intelligence for both technical and non-technical stakeholders. Additionally, this position requires expertise in predictive modeling, data governance frameworks, and the ability to translate organizational data strategy into operational reality while partnering cross-functionally with product, engineering, and leadership teams. Experience in regulated industries that require data sovereignty — such as financial services, government, or healthcare — is strongly preferred. Compensation will be commensurate with experience, and equity options are available. EOE.

Responsibilities

• Architect the analytics platform that transforms raw data into the insights powering every decision we make.
• Own the data strategy that connects every corner of our organization to smarter, faster decisions.
• Design the secure, scalable analytics backbone that turns complex data into clear action.
• Designing scalable data infrastructure and ingestion frameworks that consolidate diverse data sources into a unified platform.
• Integrating cross-functional metrics from operational performance, user engagement, platform utilization, and business outcomes into a cohesive analytics layer.
• Working within a sovereign data environment built to enterprise-grade security standards and establishing data governance protocols.
• Oversee a team of data scientists and engineers, fostering a collaborative and productive environment across onsite and distributed teams. Draft and manage the production of academic papers, showcasing the team’s innovations and contributions to data science.

Requirements

• 8+ years of experience building enterprise analytics platforms or business intelligence systems at scale.
• Expertise in predictive modeling and data infrastructure design.
• Experience with multi-modal data generation (text, image, video) and the ability to leverage this in creating innovative AI solutions.
• Strong background in managing the software and hardware infrastructure for AI/ML projects.
• A proven ability to translate organizational data strategy into operational reality.

Qualifications

• Proven leadership skills with experience managing onsite and distributed data science teams.
• Ability to communicate complex data science concepts effectively, internally and in the academic community, with a history of publishing scholarly papers.
• Proficiency in a wide range of data science tools and platforms, with the flexibility to adopt new technologies and methodologies as required.