Intern Sustainability large language model (LLM) and text analytics data science

Internship Opportunity: Sustainability Large Language Model (LLM) and Text Analytics Data Science

Within FrieslandCampina, we have an ambitious sustainability strategy driven by both passion and data.

While numerical data is standard for tracking commitments, there are also large volumes of qualitative, text-based data points that require data-driven approaches. This internship focuses on using the latest technologies to help our sustainability colleagues analyze text in the same data-driven way as we do with numeric key performance indicators (KPIs) and commitments.

What we ask

• Enrolled in a relevant university program with a focus on data analysis and/or sustainability
• Programming skills, ideally in Python and PySpark (this is a must)
• Experience in SQL, Databricks, and AZURE knowledge (this is a plus)
• Knowledge of text analytics techniques and experience and/or interest in dealing with large pieces of text and documents programmatically
• Can-do mentality towards solving tasks that require acquiring new skills quickly

What we offer

We offer an interesting and challenging internship position, providing you the opportunity to develop yourself in your field. You can count on sufficient professional supervision and a reasonable internship allowance.

Job Description

In this position, you will be working on:

• Developing generic methodologies around extraction, validation, and verification of text-based data (data science part)
• Scaling these analytics insights (engineering part of the internship) to enable insights from a large number of documents
• Supporting sustainability colleagues in extracting and visualizing results from text

Team Details

In this position, you will be located between the Corporate Sustainability and sustainability analytics group. You will work with a multidisciplinary team located in the innovation center in Wageningen and/or Amersfoort offices, supporting a variety of FrieslandCampina internal stakeholders with data and analytics (D&A) insights.