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About the Role

As a Data Scientist specializing in generative artificial intelligence, you will contribute to the design, evaluation, and industrialization of high-value AI solutions for Wealth & Asset Management businesses. You will be involved from understanding business needs to validating models and prototypes, working with various technical and functional profiles.

Responsibilities

Design, develop, and test generative artificial intelligence solutions that address concrete business needs, such as conversational assistants, generation-augmented search systems, document extraction tools, analysis workflows, or decision support systems.
Prepare, structure, and analyze the data required for AI use cases, ensuring its quality, relevance, traceability, and compliance.
Define and implement evaluation frameworks for models and generated responses, including functional tests, performance measurement, hallucination risk analysis, robustness, and business relevance.
Collaborate with Data Engineering and platform teams to industrialize AI solutions, covering integration, deployment automation, monitoring, observability, environment management, and production readiness.
Document models, datasets, architectural choices, known limitations, and evaluation results to ensure traceability and proper governance of solutions.
Support business users in qualifying needs, formalizing use cases, interpreting results, and adopting AI solutions.
Participate in technological watch, experimentation, proof of concepts, and identification of new generative artificial intelligence use opportunities.

Requirements

Proven experience in data science, ideally gained in a banking, financial, consulting, or highly regulated environment.
Solid command of Python and key data science, machine learning, and natural language processing libraries.
Good understanding of classical machine learning models and associated statistical principles: classification, regression, clustering, time series, NLP.
Experience with or good understanding of generative artificial intelligence architectures: large language models, generation-augmented search, prompt engineering, prompt evaluation, information extraction, AI chain or workflow orchestration.
Knowledge of language model optimization mechanisms, such as finetuning, quantization, distillation, or equivalent techniques, is valued for industrial applications.
Good understanding of Deep Learning fundamentals and agentic AI systems.
Experience with Azure OpenAI Service, Azure AI Foundry, or equivalent AI development and evaluation environments.
Knowledge of Azure Document Intelligence, Microsoft Fabric, PySpark, or equivalent data cloud environments is appreciated.
Understanding of MLOps best practices: versioning, testing, integration and deployment pipelines, monitoring, observability, documentation, and production deployment.
Strong sensitivity to data governance, security, confidentiality, compliance, and AI risk management issues.
Ability to understand complex business problems and translate them into concrete, testable, and industrializable analytical or AI solutions.
Methodological rigor, analytical skills, documentation proficiency, and attention to the quality of deliverables.
Teamwork aptitude and ability to collaborate with diverse stakeholders: business units, Product Owners, Data Scientists, Data Engineers, platform, security, and compliance teams.
Autonomy, technological curiosity, pragmatism, and ability to experiment quickly while respecting the constraints of a regulated environment.
Communication and pedagogical skills to make AI topics accessible to non-technical stakeholders and promote solution adoption.

Skills

Data Science
Machine Learning
Artificial Intelligence
Generative AI
Python
Natural Language Processing (NLP)
Large Language Models (LLMs)
Prompt Engineering
MLOps
Data Analysis
Data Preparation
Model Evaluation
Solution Industrialization
Deep Learning
Agentic AI Systems
Azure OpenAI Service
Azure AI Foundry
Azure Document Intelligence
Microsoft Fabric
PySpark
Data Governance
Data Security
Confidentiality
Compliance
Risk Management

Location

40 countries

Work Type

Full-time

Experience Level

3 to 5 years minimum experience in data science, machine learning, or applied AI, with significant exposure to generative artificial intelligence.

About the Company

Rothschild & Co is a leading international financial services group, family-controlled for seven generations and at the heart of financial markets for over 200 years.
Our expertise, know-how, and global network provide a unique perspective that benefits the business and wealth of our clients and stakeholders, while respecting our planet.
Our teams of 4,200 financial advisory specialists on the ground in over 40 countries bring a unique international vision across four leading businesses: Global Advisory, Wealth Management, Asset Management, and Five Arrows.
As a family-based group founded on human relationships, we place particular importance on recruiting and developing our employees' careers so they can thrive professionally.