Data Scientist

Our requirements

• 3+ years in statistics and machine learning.
• Strong PL/SQL skills and hands-on work with Autonomous Database (ADW) on OCI.
• Practical knowledge of OCI Data Science: notebook sessions, Jobs, ML Pipelines, conda environments, Model Catalog (versioning, metadata) and Model Deployment.
• Model monitoring for drift and performance.
• Working with Autonomous Database and Object Storage from Data Science, with a clear view on when to train in-database vs. externally.
• Scheduling and orchestration of batch scoring on daily-refreshed data.
• Background in LLM- and RAG-based solutions, ideally on OCI Generative AI, including hosting or calling LLMs in governed agents.
• Ability to build agents that query governed data through SQL and function-calling tools instead of answering numbers from model memory.
• Solid grasp of retrieval fundamentals: chunking, embeddings, retrieval quality evaluation.
• Solid grasp of guardrails and traceability: prompt-injection controls, citations, trace logging of every tool call and answer, human approval for consequential actions.
• Good command of cloud security: IAM policies, Vault, private networking, Logging and Monitoring.
• Fluent English (min. B2).

Optional

• Oracle Machine Learning (OML) and Select AI, including where Select AI fits and where it doesn’t.
• Familiarity with OCI Generative AI Agents: agents, endpoints, sessions and knowledge bases over documents such as policy wordings, underwriting guidelines, actuarial memos and FWA investigation playbooks.
• Exposure to Oracle AI Vector Search or OpenSearch.
• Exposure to OCI Data Flow (Spark).
• Insurance domain knowledge (underwriting, actuarial, FWA).
• Background in multi-tenant solutions that keep client data and models isolated.

Your responsibilities

• Build ML and statistical models (e.g. risk scoring, fraud detection) for insurance clients on OCI.
• Prepare data and manage the model lifecycle: training, batch scoring, deployment and drift monitoring.
• Run daily batch scoring and large-scale data processing.
• Design GenAI agents with RAG over insurance documentation and governed access to data through SQL.
• Build and evaluate the vector search layer behind the agents.
• Implement guardrails and traceability for GenAI solutions.
• Ensure security and isolation of client data in a multi-tenant setup.

About the project

What we offer

• We focus on long-term relationships based on fair principles and reliability.
• Co-financing of the Multisport card and Medicover private healthcare.
• Modern office available.
• Team bonding activities, internal courses, conferences, certifications.

Benefits

• sharing the costs of sports activities
• private medical care
• sharing the costs of professional training & courses
• integration events