Senior Data Scientist - Observe-to-Agent (O2A) Platform

Senior Data Scientist - Observe-to-Agent (O2A) Platform

Job Overview
The Senior Data Scientist will lead the advanced Enterprise Data Science strategy for the Observe-to-Agent (O2A) platform-an enterprise capability that transforms video-based process captures into actionable agentic workflows and automation code. This role drives multimodal analytics, workflow automation, and enterprise data science adoption, enabling operational efficiency across the COO organization and enterprise-wide functions.



Key Responsibilities

Enterprise Data Science Capability Development

• Lead the design, implementation, and scaling of the Observe capability, ensuring consistent, secure, and measurable data-driven deployment across business units.
• Develop agentic data models that convert raw video captures and telemetry into executable workflows/code, accelerating automation across operations and enterprise functions.
• Own end-to-end data pipelines, including video ingestion, feature extraction, clickstream analysis, semantic modeling, and structured insights generation.

Data Science Roadmap & Multi-Release Planning

• Define the enterprise data science roadmap and multi-release strategy for the Video-to-Code pipeline and agent creation ecosystem.
• Integrate multimodal learning, semantic understanding, and hybrid deterministic + probabilistic architectures aligned to enterprise priorities.
• Establish scalable frameworks for video-to-API code generation and workflow automation, enabling rapid delivery and measurable operational impact.

Integration & Enterprise Analytics

• Define governance standards, model risk controls, PII management, and safe-use patterns for data-driven systems.
• Develop experimentation frameworks to validate models, monitor drift, and ensure robust deployment in cloud and containerized environments.

Advanced Enterprise Data Science Innovation

• Lead research and development of multimodal and generative data models (e.g., large action or behavior models) for workflow automation.
• Build foundational data services, including knowledge graph generation, semantic mapping, ontology design, automated workflow generation, and structured insights extraction.
• Identify high-value automation and analytics opportunities via process mining, behavioral clustering, and anomaly detection.

Cross-Functional Leadership

• Partner with engineering, data ops, platform teams, and business stakeholders to translate enterprise data into actionable insights and automated solutions.
• Define quality, observability, and assurance metrics for data pipelines, including SLA monitoring, execution rollback, validation checkpoints, and alerting frameworks (ARIZE, Phoenix, Splunk).
• Influence enterprise data science strategy, prioritization, and deployment decisions at senior leadership levels.

Enterprise Strategy & Change Leadership

• Establish data release, monitoring, and change-management routines for enterprise adoption.
• Mentor and guide cross-functional teams in model deployment, experimentation frameworks, and observability practices.
• Deliver transformative enterprise data science solutions that require creativity, advanced analytical reasoning, and operational scalability.
• Serve as a trusted advisor on enterprise data science innovation, workflow automation, and large-scale digital transformation initiatives.

Required Qualifications

• 7+ years of experience in enterprise data science, applied analytics, or data-driven solution leadership, including enterprise-scale deployments.
• Technical expertise in multimodal data science, workflow automation, agentic modeling, and enterprise-scale analytics pipelines.
• Proven ability to define, scale, and deploy enterprise-grade data science solutions.
• Strong systems-thinking mindset with experience designing operationally scalable and compliant data systems.
• Track record of collaborating with senior leadership and cross-functional teams to influence data science strategy and delivery.
• Experience delivering complex enterprise data science services across multiple engineering or analytics teams.