Senior Data Scientist
Dataiku provides an enterprise AI platform for building, deploying, orchestrating, and governing analytics, machine learning, generative AI, and AI agents. Its customers include large organizations across financial services, life sciences, manufacturing, retail, energy, logistics, technology, and the public sector.
About Dataiku
Dataiku develops a unified enterprise AI platform that connects people, data, analytics, machine-learning models, large language models, and AI agents in a governed environment. Its offerings include AI-agent development and orchestration, centralized LLM management, AI governance, trusted analytics, machine-learning development and deployment, collaboration, monitoring, lineage, and risk controls. Dataiku serves enterprise business and technical teams, including organizations operating in complex and highly regulated industries.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will design and deliver production-grade AI projects with customers, covering data integration, pipeline design, solution architecture, and deployment. You will lead architecture trade-offs, support user training, shape technical proposals, provide strategic guidance, and coordinate delivery sprints and priorities.
Requirements
- 8 years of experience in advanced analytics and AI
- 5 years of hands-on experience with Python and SQL
- 5 years of experience designing, building, and deploying production-grade AI and machine learning models
- Experience owning technical outcomes directly with customers
- Ability to communicate complex concepts to technical and non-technical audiences
- Experience using large language models, agents, and machine learning
- Understanding of cloud architectures, Hadoop, or Kubernetes
Responsibilities
- Design and co-develop production-grade AI projects with customers
- Train and support users on the Dataiku platform
- Contribute to end-to-end solution architecture, data integration, pipeline design, and deployment
- Make and defend architecture trade-offs
- Provide strategic guidance to customers and account teams
- Scope technical solutions and estimate delivery effort
- Coordinate sprints, prioritize tasks, and estimate delivery effort