Senior AI Data Scientist, Agentic Automation
Pubblicato il 03-10-2026 - Team.Blue in Italia
Overview As Senior Data Scientist in the Applied AI team, you will build agentic marketing-automation systems that span multiple brands and languages. You map processes, quantify ROI, and deliver production-ready solutions that operate end-to-end and credibly justify decisions. You'll shape auditable, self-documenting workflows and deploy them with guardrails, ensuring safe, scalable influence on marketing outcomes. This role blends data science with software engineering to drive measurable impact across SMB brands.
Responsabilità
Map current marketing workflows and attach hours per step to quantify effort
Extract live requirements from non-technical stakeholders
Design state transitions, API calls, and failure handling across steps
Build guardrails: dry-run mode, approval gates, least-privilege scopes, undo mechanisms
Define human-in-the-loop policy and review queues for marketers
Write evaluation designs for non-traditional metrics (precision/recall, source verification, brand voice checks)
Validate tracking data quality and quantify errors before production
Integrate agents with webhooks or scheduled triggers and ensure idempotent behavior
Decide when to use frontier vs cheaper models and prove cost/latency tradeoffs
Evaluate vendor APIs, rate limits, data models, integration costs
Ensure safety: staging modes, approvals, auditability, and rollback paths
Ship end-to-end: code, containerise, instrument, deploy with minimal DevOps support
Requisiti fondamentali
~7+ years building data and ML systems
~ Expert in Python and ML
~ End-to-end production experience with multi-step, tool-calling LLM workflows
~ Experience integrating with third-party APIs, including auth, rate limits, pagination
~ Cost and latency optimization in model routing and caching
~ Safety-focused design with staging, approvals, least-privilege scoping
~ Evaluation design for generative/agentic output (calibration, regression suites, red-teaming)
~ Process mapping and quantitative analysis of work