- Company Name
- Medical Guardian
- Job Title
- Director of Data Science and AI Automation
- Job Description
-
Job title: Director of Data Science and AI Automation
Role Summary:
Lead the end‑to‑end data intelligence and AI automation function, overseeing a multidisciplinary team (Data Science, Analytics Engineering, Automation Engineering, ML Ops). Own the full lifecycle of predictive modeling, real‑time reporting, and intelligent workflow orchestration. Partner with engineering, product, operations, and executive leadership to deliver scalable, business‑impactful AI and automation solutions.
Expactations:
- 8+ years in Data Science, ML, Analytics, or Automation with a minimum of 4 years in leadership.
- Proven ability to build and scale high‑performance teams and deliver measurable business outcomes.
- Experience with cloud‑native AI/ML infrastructures, especially Azure (Event Hub, Service Bus, Functions, Databricks).
- Strong communicator with executive‑level stakeholder engagement skills.
Key Responsibilities:
- Design, develop, and deploy production‑grade predictive models (risk scoring, personalization, forecasting).
- Own ML architecture: feature stores, pipelines, model retraining, validation, monitoring, and governance.
- Build and maintain enterprise reporting and BI stack (Power BI, Snowflake, Databricks, APIs).
- Deliver executive dashboards, KPI frameworks, forecasting tools, and operational reports.
- Lead automation strategy: orchestrate workflows with n8n, Make.com, Azure Logic Apps, Zapier, custom Python, and "vibe coding".
- Automate critical internal processes across Operations, Care, Sales, Finance, and Engineering.
- Set standards for experimentation, documentation, reproducibility, and operational excellence.
- Create, prioritize, and execute the cross‑company AI/automation roadmap.
- Advise executives on data strategy, AI capabilities, automation opportunities, and business impact.
Required Skills:
- Expertise in Python, sklearn, PyTorch/TensorFlow, Databricks ML, and ML Ops tooling.
- Proficiency in BI tools (Power BI, Snowflake, Databricks, API integrations).
- Experience with automation platforms (n8n, Make.com, Azure Logic Apps, Airflow) and rapid “vibe coding” workflows.
- Deep knowledge of cloud ecosystems with Azure preferred; familiarity with event‑driven triggers and serverless functions.
- Strong data governance, security, compliance, and ML monitoring acumen.
- Familiarity with generative AI/LLM integration, agentic workflows, and orchestration platforms.
Required Education & Certifications:
- Bachelor’s degree in Computer Science, Engineering, Statistics, Applied Math, or related field (master’s preferred).
- Relevant certifications (e.g., Azure Data Scientist Associate, Microsoft Certified: Azure AI Engineer Associate, or equivalent).
Philadelphia, United states
Hybrid
Senior
04-03-2026