Dataiku’s mission is big: to enable all people throughout companies around the world to use data by removing friction surrounding data access, cleaning, modeling, deployment, and more. One of the most unique characteristics of our product, Data Science Studio (DSS), is the breadth of its scope and the fact that it caters both to technical and non-technical users. Through DSS, we aim to empower people through data, democratize data science, and to make our everyday AI ambition a reality.

To accelerate our everyday AI mission, Dataiku’s Business Solutions team is in charge of creating a full range of solutions aiming at easing delivery of key use-cases by our customers.

Dataiku is looking for a Senior Solutions Data Scientist to join Dataiku’s Business Solutions team. In this role, the Senior Solution Data Scientist will focus on creating and supporting go-to-market solutions. Through interactions and detailed work with Dataiku partner community and customers, the Senior Solution Data Scientist will play a key role in identifying industry specific needs, scope use-cases, and build “ready-to-use” solutions. This mission will be run in tight partnership with the Solutions Director, the rest of the Business Solutions team, and all other Dataiku teams, including Data Fab, Sales, Customer, Partnerships, Product and R&D.

Responsibilities include (but are not limited to):

• Work tightly with relevant Solution Consultants on building a our Solutions roadmap for a given set of business functions or business objectives. This roadmap will be fuelled by a variety of signals, including market evolutions, customer experiences, partner initiatives, specialized data and ISV players. The Solution Data Scientist will notably be asked to develop strong relationships with a range of trusted customers and partners, ensuring constant support on roadmap construction and delivery. They will be encouraged to develop a process consulting mindset, developing a detailed understanding of specific business user needs so as to fully assess (and close) the gap between their day-to-day data-driven needs and how Dataiku can support them.

• Own the building and delivery of resulting projects, from ideation to full roll-out. As part of this, the Solution Data Scientist is in charge of the delivery of pre-built use-cases (flow, visualization, packaging), creation of replicable assets (plugins, integrations, …), documentation, testing, … The Solution Data Scientist will also own the building and delivery of future evolution roadmap for each solution.

• Tightly work with other Solutions Data Scientists on their projects. Gradually develop business function domain expertise to become a go-to-person on subjects to certain business lines for the Dataiku Data Science community and Sales Engineering teams.

• Be a key stakeholder in the initial roll-out of resulting Solutions in the market: customer demos, customer implementations, partner training, marketing, enablement of all other Dataiku team members (ie. Data Fab, Sales Engineering, …).

• Be an active member of Dataiku’s Solutions Engineering group: support building of our overall engineering roadmap, contribute to capitalization and technical research for the team, own key transversal projects, and more.

Success Profile:

• 5+ year total experience minimum, with deep hands-on experience on data science projects, with strong understanding of integration in business processes
• Proven track record of scoping and managing data-science projects in an autonomous manner
• Ability to work in a global, distributed team. Strong communication skills, with capacity to adapt level of technicity and speech to a wide range of audience
• Appetite for client facing engagement and proven capacity to deliver top quality documentation and marketing content (blog posts, step-by-step flows, …)
• Strong appetite for data science use-case packaging and willing to develop an engineering mindset: keen to turn outcomes into easy to understand visualizations, explore integrations with other tools, build reusable building blocks, mindful of production constraints
• 2+ years of experience with R or Python
• 2+ years of hands on experience with data ETL, cleaning, and machine learning algorithms
• Knowledge of NLP, deep learning, reinforcement learning, knowledge graph, and causal inference methodologies
• Experience with life sciences data model concepts and standards including OMOP, FHIR, and FAIR will be a plus
• Experience developing WebApps (Javascript,Dash or RShiny..)
• Curious, eager to learn and explore, extremely structured and autonomous