Data Science - Operational Research Internship (6 months from Feb/March)
At Dataiku, we're not just adapting to the AI revolution, we're leading it. Since our beginning in Paris in 2013, we've been pioneering the future of AI with a platform that makes data actionable and accessible. With over 1,000 teammates across 25 countries and backed by a renowned set of investors, we're the architects of Everyday AI, enabling data experts and domain experts to work together to build AI into their daily operations, from advanced analytics to Generative AI.
This is a golden age for business AI applications, thanks to a frantic rate of scientific research, a culture of openness with many scientific publications, models, and software libraries freely available, and increasing results directed towards concrete, practical tasks. At Dataiku, we help our customers leverage cutting-edge mathematical and AI techniques to solve complex problems at scale.
In this context, the internship will study advanced optimization techniques, implement them in a realistic business scenario, and create technical assets (such as a blog post and a sample project) to help Dataiku users leverage these techniques for concrete use cases.
Responsibilities:
- Study recent advancements in operations research, focusing on techniques such as linear programming, mixed-integer programming, stochastic optimization, or network flows.
- Implement optimization models in Python to solve a realistic use case that can be generalized across industries.
- Create a public demo and technical blog post to showcase how optimization models can be applied in Dataiku.
- Present your work to internal teams, including data scientists and solution engineers, to support customer-facing teams with new insights.
- If the opportunity arises, contribute to a proof-of-concept project with a Dataiku customer to apply the developed optimization techniques in a real-world setting.
Requirements:
- Currently pursuing a Master’s degree in Operations Research, Machine Learning, Computer Science, Mathematics, or a related field.
- Exposure to optimization techniques such as linear, mixed-integer, or non-linear programming.
- Proficiency in Python and experience with optimization libraries (e.g., Gurobi, CPLEX, or similar tools).
- Curiosity, strong problem-solving skills, and a willingness to explore new techniques for solving complex business problems, such as supply chain optimization, network flow, demand forecasting, and resource allocation, all within the Dataiku platform.
- Strong written and verbal communication skills.
- Fluent English and French.
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