About this role
You will design and co-develop production-grade AI projects with customers across diverse industries, acting as the technical authority and trusted advisor from initial workshops to production impact. Working directly within the Dataiku platform using Python and SQL, you will embed with client teams to architect end-to-end solutions, guide platform adoption, and train client leadership.
Dataiku provides an enterprise orchestration layer for building, deploying, and governing AI across multi-vendor environments. This customer-facing role requires deep technical capability combined with strong communication skills, as you will balance client constraints, make architecture trade-offs, and coordinate delivery sprints while owning technical outcomes.
What you will do
- Design and co-develop production-grade AI projects with customers across a wide range of industries and use cases.
- Enable users to discover and master the Dataiku platform through training sessions, office hours, workshops, and ongoing consultative support.
- Embed directly with client data, business, and engineering teams to contribute to end-to-end solution architecture from data integration to production deployment.
- Make and defend key architecture trade-offs regarding native platform functions versus custom code and batch versus real-time processing.
- Provide strategic guidance to customers and account teams to help drive adoption, value realization, and long-term success.
- Contribute to shaping solutions and building compelling proposals, including technical scoping and effort estimation.
- Help drive efficient customer engagements by coordinating sprints, prioritizing tasks, and estimating delivery effort.
What you need
- Bring 8 years of experience in Advanced Analytics and AI, ideally in a consulting or customer-facing data science and AI solution engineering role.
- Demonstrate 5 years of hands-on experience using Python and SQL.
- Possess 5 years of experience designing, building, and deploying production-grade AI and machine learning models.
- Show a proven track record of owning technical outcomes directly with customers through consulting, professional services, or embedded delivery models.
- Exhibit strong empathy, collaboration skills, and the ability to communicate complex concepts clearly to both technical and non-technical audiences.
Nice to have
- Experience using Large Language Models, Agents and Machine Learning to build innovative, real-world applications
- Experience with data visualization, including building applications using frameworks such as Dash, Streamlit, RShiny or JavaScript
- Experience consuming and/or building APIs
- Experience with Data Engineering and MLOps practices
- Understanding of cloud architectures, as well as systems such as Hadoop or Kubernetes
Skills and tech stack
Questions candidates ask
What programming languages are used daily in this role?
Data scientists work in the Dataiku platform every day, primarily using Python and SQL, with occasional work in other languages such as R, PySpark, and JavaScript.
What does the day-to-day customer interaction involve?
You will embed directly with client data, business, and engineering teams to co-design AI solutions, run training sessions, make architecture trade-offs, and guide platform adoption from initial workshops to production impact.
What background is expected for applicants?
Candidates should have 8 years of experience in Advanced Analytics and AI, ideally within a consulting or customer-facing data science and AI solution engineering role, along with 5 years of hands-on experience with Python, SQL, and production-grade model deployment.