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Scalian

Engineering and consulting in AI avionics

Architecte Data / IA

Data ManagementConfirmed live in the last 24 hours
Full-timeRennes, FranceNo salary listed

About the Job

Requirements

  • 10 to 15 years of experience, including at least 5 years in Data/AI architecture in financial services.
  • Significant experience delivering at least two Data/AI projects into production in the financial-services sector.
  • Engineering education, a business-school qualification with strong technical specialization, or equivalent university-level Bac+5 education.
  • Mastery of Data/AI architectures in regulated environments and of explainability, traceability, and robustness requirements.
  • Good understanding of banking, insurance, or asset-management business domains.
  • Ability to contribute to presales and solutioning, then own architecture during delivery of complex projects.
  • Ability to structure an industrialization approach, including prerequisites, phases, deliverables, risks, costing, and deployment roadmap.
  • Ability to engage with decision-makers, business teams, Data/AI teams, cloud teams, and delivery teams.
  • Ability to document reusable patterns, develop practice assets, and equip teams.
  • Desired technical skills include Databricks or Snowflake, Delta Lake, Kafka, Airflow, Spark, MLflow, Vertex AI or SageMaker, feature stores such as Tecton or Feast, Hugging Face, LangChain, LlamaIndex, RAG architectures, fine-tuning, AWS, Azure or GCP, sovereign or private cloud such as OVHcloud, Outscale or S3NS, Kubernetes, Docker, Terraform, Python, and SQL.
  • Knowledge of financial-services domains and capabilities including scoring, pricing, fraud, KYC/AML, risk, compliance, actuarial work, trading, and customer relations.

Responsibilities

  • Define Data/AI architectures, including data mesh, feature stores, MLOps platforms, scoring, pricing, and generative AI for augmented advisors.
  • Industrialize solutions, ensuring scalability, performance, resilience, and cost control.
  • Translate the requirements of the AI Act, DORA, ACPR, GDPR, Basel, and Solvency into design decisions.
  • Ensure model explainability, traceability, robustness, and bias control.
  • Integrate business constraints across risk, compliance, anti-fraud, KYC/AML, marketing, customer relations, actuarial work, and trading.
  • Capture reusable patterns and develop reusable scoring, pricing, and anti-fraud components.
  • Contribute to commercial proposals and client scoping.
  • Develop the offering, build initial references, and deliver expertise on client projects.
  • Contribute to development of the Data/AI practice, its assets, and references.

Desired Qualifications

  • Technical experience with Databricks or Snowflake, Delta Lake, Kafka, Airflow, Spark, MLflow, Vertex AI or SageMaker, Tecton or Feast, Hugging Face, LangChain, LlamaIndex, RAG architectures, fine-tuning, AWS, Azure or GCP, OVHcloud, Outscale, S3NS, Kubernetes, Docker, Terraform, Python, and SQL.

About the Company

Scalian

Engineering and consulting in AI avionics

Scalian Group provides engineering and consulting services to multiple industries, with a focus on AI, avionics, and information systems security. It helps clients by offering tailored solutions built from consulting, managed security services, and software offerings. The company works by combining advisory work, implementation support, and ongoing security and software management to meet each client’s specific needs. What sets Scalian apart is its emphasis on an agile approach and its deep, industry-specific expertise in aerospace and security, enabling rapid adaptation and high-performance results for global industrial leaders. The company aims to deliver precise, reliable solutions that improve performance, security, and efficiency for its clients.

Company size
1,001-5,000
Company stage
Acquired
Total funding
$612.7M
Headquarters
Labège, France
Founded
1989

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