Director of Data Science and AI Automation

Role

The Director of Data Science and AI Automation will lead data intelligence, machine learning, reporting, and automation across the organization. This role owns end-to-end model development, realtime decisioning, ML Ops, reporting, and automation initiatives, and leads a multidisciplinary team spanning Data Science, Analytics Engineering, Automation Engineering, and ML Ops.

Key Responsibilities

• Lead end-to-end development of predictive models, personalization engines, risk scoring, forecasting, and optimization frameworks.
• Oversee ML architecture, feature stores, pipelines, model retraining, validation, monitoring, and governance.
• Implement production-grade ML Ops aligned with realtime decisioning layers (Azure, Databricks, event-driven triggers).
• Build a roadmap for intelligent automation and generative AI-powered capabilities.
• Own the reporting and analytics stack (Power BI, Snowflake, Databricks, APIs, data ingestion) and deliver executive dashboards, operational reporting, forecasting tools, and KPI frameworks.
• Partner with Data Engineering on data models, semantic layers, governance, quality checks, and observability.
• Design and deploy automation initiatives using n8n, Make.com, Azure Logic Apps, Zapier, and custom Python workflows; automate workflows across Operations, Care, Sales, Finance, and Engineering.
• Implement lightweight, rapid “vibe coding” automations and human-in-the-loop AI automations; drive adoption of event-driven and AI-assisted process automation.
• Build and mentor a high-performing team; establish standards for experimentation, documentation, reproducibility, and operational excellence.
• Advise executives on data strategy, AI capabilities, automation opportunities, prioritization, and business impact.

Requirements

• 8+ years of experience in Data Science, ML, Analytics, or Automation roles, with at least 4+ years in leadership.
• Expertise in ML frameworks and libraries (Python, sklearn, PyTorch, TensorFlow, Databricks ML) and modern BI environments.
• Experience with automation tools such as n8n, Make.com, Azure Logic Apps, Zapier, and orchestration tools like Airflow.
• Strong understanding of cloud ecosystems (Azure preferred) including Event Hub, Service Bus, Functions, Databricks, and APIM.
• Experience building automation and AI-powered workflows across operational departments and implementing ML monitoring, governance, compliance, and security.
• Experience with generative AI, LLM integration, and agentic workflows or orchestration platforms.
• Proven record of owning a multidisciplinary team and delivering measurable business results.
• Excellent communication and executive-facing stakeholder management skills.
• Authorization to work in the United States without visa sponsorship and ability to work from the Philadelphia office on Tuesdays and Wednesdays.