6 meilleures offres (data analytics engineer h/f, paris, a8) (à pourvoir)

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Chief AI Officer - Groupe HARVEST - Paris - H/F

Harvest -
Paris (75)

Postuler rapidement

Détails de l'emploi

CDI | Temps plein

Qualifications

TensorFlow
Power BI
Azure
PyTorch
Anglais
Tableau
Master
Ingénierie informatique
Intelligence artificielle
Leadership
Python

Description complète du poste

FinTech leader en France pour les logiciels dédiés aux métiers du patrimoine et de la finance, HARVEST accompagne les professionnels avec des solutions couvrant toute la chaîne de valeur patrimoniale et financière depuis 35 ans. Le groupe conçoit des solutions digitales, rend accessible l’information indispensable pour éclairer les décisions patrimoniales et financières. Spécialiste de la data, il permet la construction automatisée de portefeuilles efficients sur mesure.
Avec plus de 4600 sociétés clientes, le groupe propose un ensemble de logiciels et de services plébiscités par les professionnels désireux de développer un conseil à forte valeur ajoutée.

Expertise métier et maîtrise technologique s’exercent avec plus de 600 talents passionnés et investis. Le groupe a recruté plus de 100 collaborateurs en France en 2024 pour accompagner sa croissance et son ambition de devenir le champion européen de la WealthTech.

Description du poste

ROLE OVERVIEW

As our Chief AI Officer 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:

Define and execute the company-wide AI strategy.
Co-build roadmaps with Product Managers and steer discovery/delivery for AI-powered features.
Identify, launch, and maintain internal AI and Data initiatives that lift productivity and quality.
Grow and coach a multidisciplinary squad (AI Engineer, Data Analyst, Data Engineer).

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, make sure 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.

Profil recherché

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.
Fluent in English

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