Data Scientist Internship
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您的使命 我们的工程团队 我们的工程团队负责开发我们的SaaS平台并构建全面且用户友好的产品。Pigment工程师参与整个应用程序开发生命周期，专注于设计、编码以及保持生产平台的正常运行。他们可以专业化，但基础设施、后端和前端之间没有严格的区分。 我们重视以用户为中心和务实精神：我们选择最适合解决问题的工具，了解每种技术的优势和局限性……
必备技能
免费注册后解锁"你的匹配分 vs 高分画像"与个人技能缺口。
职位描述 · 原文
Your mission
Our Engineering team
Our Engineering team is responsible for developing our SaaS platform and building a comprehensive and user-friendly product. Pigment engineers participate in the entire application development lifecycle, focusing on design, coding, and keeping the production platform up and running. They can be specialized, but there is no strict separation between infrastructure, backend, and frontend.
We value user-centricity and pragmatism: we choose the most relevant tools for the problem we have to solve, understanding the strengths and constraints of each technology. Our engineering culture also values curiosity, humility, trust, ownership, and team spirit.
👉 Curious to see what we’re building? Check out our Tech Blog !
As a Data Scientist Intern, you will help us push the boundaries of what AI can do inside Pigment, focusing on how our AI Modeler builds and maintains planning models. You’ll work closely with our AI engineering and data science teams to design, test, and evaluate LLM-based systems that turn loosely structured inputs into reliable, working Pigment models and formulas.
Project Overview: Making Pigment’s AI Modeler Smarter
Depending on your profile and interests, you will focus on one of these topics:
1. Formula Writing from Specifications
Have the Modeler write a specification of a formula (what it should do, and the tests it must pass), then build a small Formula Writer model that produces a correct formula from it.
2. Building Models from External Documents
Turn amorphous inputs (long PDFs, call transcripts, existing applications, templates) into structured Pigment applications: write the tests first, then iterate on a DSL representation until they pass.
3. Building Models from Databases
Given an existing database, determine which blocks and transformations to create to make sense of the data and integrate it as a Pigment model.
As an intern, you will:
Define success criteria, test suites, and evaluation metrics for your topic.
Design and iterate on LLM-based approaches (prompting, agentic workflows, intermediate representations).
Benchmark quality, reliability, and cost/latency, and document trade-offs.
Work with engineers and data scientists to build evaluation pipelines and share findings.
Technical Stack
Our current AI and engineering stack includes:
Languages & Frameworks: Python, LangGraph
Data & ML Infrastructure: Weights & Biases, Hugging Face Hub, Google Cloud Platform (GCP), Docker, Kubernetes
Databases: PostgreSQL
CI/CD & Experimentation: CircleCI, MLflow, and internal orchestration tools
We don’t expect you to know them all. What matters most is your ability to learn quickly, experiment rigorously, and translate data insights into actionable results.
Work Environment
Hybrid: possibility to work partially remotely
Office in the heart of Paris (Paris 9)
Choose your working environment (hardware / OS)
A competitive remuneration package
Opportunity to continue your journey with us after your internship
Technical stack
Our current AI and engineering stack includes:
Languages & Frameworks: Python, LangGraph
Data & ML Infrastructure: Weights & Biases, Hugging Face Hub, Google Cloud Platform (GCP), Docker, Kubernetes
Databases: PostgreSQL
CI/CD & Experimentation: CircleCI, MLflow, and internal orchestration tools
We don’t expect you to know them all. What matters most is your ability to learn quickly , experiment rigorously , and translate data insights into actionable results .
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公司 · Company
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