The role of a Data Scientist at Dataiku is quite unique. Our Data Scientists not only code up solutions to real-world problems, but also participate in client-facing endeavours throughout the customer journey. This includes supporting their discovery of the platform, helping integrate Dataiku with other tools and technologies, some user training, and co-developing data science projects from design to deployment.

Just as non-technical skills are important, so too are technical skills. Our Data Scientists work on the Dataiku platform every day. Aside from the visual tools, our team mostly uses Python and SQL, with occasional work in other languages (e.g., R, PySpark, JavaScript). An ideal candidate is excited to learn complex new technologies and modelling techniques and to explain their work to other data scientists and clients.

Key Areas of Responsibility (What You’ll Do)

• Scope and co-develop production-level data science projects with our customers across different industries and use cases
• Help users discover and master the Dataiku platform via user trainings, office hours, and ongoing consultative support
• Provide strategic input to the customer and account teams to help our customers succeed
• Provide data science expertise both to customers and internally to Dataiku’s sales and marketing teams
• Develop custom Python-based “plugins” in collaboration with Solutions, R&D, and Product teams, to enhance Dataiku’s functionality

Experience (What We’re Looking For):

• Curiosity and a desire to learn new topics and skills
• Empathy for others and an eagerness to share your knowledge and expertise with your colleagues, Dataiku’s customers, and the general public
• The ability to clearly explain complex topics to technical as well as non-technical audiences
• Over 2 years of experience with Python and SQL
• Over 2 years of experience with building ML models and using ML tools (e.g., sklearn)
• Familiarity with data visualisation in Python and R
• Understanding of underlying data systems such as Cloud architectures, Hadoop, or SQL

Bonus points for any of these:

• Experience with Consulting and/or Customer-facing Data Science roles
• Experience with Data Engineering or MLOps
• Experience developing WebApps in JavaScript, RShiny, or Dash
• Experience building APIs
• Experience using enterprise data science tools
• Passion for teaching or public speaking