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 endeavors 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 the non-technical skills are important, so too are the technical. Our Data Scientists work on the Dataiku platform every day. Aside from the visual tools, our team uses mostly python, with occasional work in other languages (e.g., R, SQL, pyspark, JavaScript, etc.). An ideal candidate is excited to learn complex new technologies and modeling techniques while being able to explain their work to other data scientists and clients.
Key Areas of Responsibility (What You’ll Do)
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Co-develop production-level data science projects with our customers.
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Analyze and investigate various kinds of data and machine learning applications across industries and use cases.
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Help users discover and master the Dataiku platform, via user training, office hours, and ongoing consultative support.
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Provide data science expertise both to customers and internally to Dataiku’s sales and marketing teams.
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Develop custom Python or R-based “plugins” in collaboration with Solutions, R&D, and Product teams, to enhance Dataiku’s functionality.
Experience (What We’re Looking For)
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Curiosity and a desire to learn new topics and skills.
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Empathy for others and an eagerness to share your knowledge and expertise with your colleagues, Dataiku’s customers, and the general public.
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The ability to clearly explain complex topics to technical as well as non-technical audiences.
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3-5 years of experience with ML tools (e.g., Python, R).
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3-5 years of experience building models.
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Familiarity with data visualization in Python and R.
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Understanding of underlying data systems such as Cloud architectures, Hadoop, or SQL.
- Travel: Up to 10% travel.
Bonus points for any of these
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Experience with Consulting and/or Customer-facing Data Science roles.
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Experience with Data Engineering or MLOps.
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Experience developing WebApps in Javascript, RShiny, or Dash.
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Experience building APIs.
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Experience using enterprise data science tools.
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Passion for teaching or public speaking.
