AI & Data Lead - Groupe HARVEST - Paris - H/F

ROLE OVERVIEW

As our AI & Data Lead you will own the end-to-end integration of AI across both to enhance products and improve operational efficiency and look after existing models and dashboards. You will:

KEY RESPONSIBILITIES

• AI Product Strategy & Roadmapping
  • Craft a clear AI vision aligned with company objectives and customer pain points.
  • Translate vision into quarterly roadmaps.
• Define success metrics, ROI models, and governance standards for AI features.
• Discovery & Delivery Leadership
  • Run discovery with customers, PMs, and designers.
  • Write PRDs, user stories, and acceptance criteria for AI/ML services.
  • Lead the AI squads through agile rituals; de‑risk delivery, control scope, and ensure model–product fit.
• AI Operations & Enablement
  • Drive AI literacy: run workshops, mentor non‑tech teams, and champion responsible‑AI guidelines.
  • Identify high‑value internal use cases and find solutions to tackle them.
• Data & Analytics
  • Maintain existing dashboards and reports and ensure data is refreshed and correct.
  • Handle simple data requests from business teams, especially CST and Finance.
  • Prioritise and answer ad‑hoc questions (KPIs, extractions, small analyses).
  • Coordinate with data engineer to keep data pipelines stable.
  • Help standardise key metrics and basic data definitions with stakeholders.
• Team Management & Talent Development
  • Set objectives, give continuous feedback, and help your three direct reports grow their craft.
  • Foster a culture of experimentation, pragmatism, and ownership.
• Stakeholder Management & Communication
  • Act as single point of contact for executives, sales, CSM, PM compliance on all things regarding AI.
  • Present roadmap progress, KPIs, and learnings in steering committees and board updates.

WHAT YOU BRING

• 7+ years in product, data, or ML engineering roles, including 2+ years leading AI/ML products end-to-end in a SaaS or fintech environment.
• Master’s in Computer Science, Data Science, Engineering, or equivalent practical experience.
• Proven ability to translate business problems into model architectures and product experiences that ship.
• Knowledge of modern BI & ML stacks (Python, TensorFlow/PyTorch, LangChain, AWS/Azure, Tableau/Power BI/Metabase).
• Strong understanding of data engineering and AI fundamentals: pipelines, warehousing, governance, observability, LLMs, RAG, fine tuning.
• Leadership experience managing small, multidisciplinary teams and collaborating with execs.
• Excellent communication skills; able to switch from deep technical discussions to C‑level storytelling.