Data Scientist Internship

Pigment; France; Híbrido; EUR 12.000 - 19.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid work

Paris office

Remuneration package

Opportunity to continue after intern

Descripción de la vacante

Pigment is seeking a Data Scientist Intern to join the Engineering team in Paris. You will help advance our AI Modeler by designing LLM-based systems, turning long inputs into structured Pigment models, and building robust evaluation pipelines.

You will work closely with AI engineering and data science teams to define success criteria, write tests, and benchmark quality, cost, and latency while contributing to the ongoing development of our DSL and model writer capabilities.

Formación

• Proficiency in Python and modern ML tooling is essential.
• Experience with LLM-driven modeling and evaluation workflows preferred.
• Ability to design experiments, write tests, and compare model variants.
• Familiarity with cloud and ML infrastructure tooling is a plus.

Responsabilidades

• Collaborate with AI and data science teams to design prompt strategies and evaluation pipelines.
• Build and iterate on LLM-based approaches to turn unstructured inputs into Pigment models.
• Benchmark model quality, reliability, and cost/latency, documenting trade-offs.
• Translate data insights into actionable Pigment features and formulas.

Conocimientos

Python

LangGraph

LLM-based systems

Prompting

Herramientas

Weights & Biases

Hugging Face Hub

Google Cloud Platform

Docker

Kubernetes

CircleCI

MLflow

Descripción del empleo

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.

Your mission

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:

• Formula Writing from Specifications
• Building Models from External Documents
• Building Models from Databases

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.

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.

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

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.