Internship - Data Analytics (Zurich, Switzerland), Zug

Vor 4 Tagen


Zug, Schweiz TN Switzerland Vollzeit

Client: Partners Group

Location:

Job Category: Other

Job Reference: 6f22c7f36f2b

Job Views: 8

Posted: 21.01.2025

Expiry Date: 07.03.2025

Job Description:

What it's about

We are looking for an Intern to join our Data Office by September 2024 for 4 to 6 months.

The main tasks will be the following:

  • Analyze data about companies in the CRM and Investment sourcing system and develop a model that identifies uniqueness, proposing cleansing actions to data stewards.
  • Analyze data about companies across various systems, including the mapping from disparate application models to the unified model of the master data system, to propose de-duplication & mapping logic to be applied during data integration & mastering.
  • Apply PG's AI LLM solutions to prototype an implementation that recognizes core entities within unstructured documents leveraging the pre-trained models with vectorized additional proprietary Partners Group input.

What we expect

  • Top performing students in the final phase of their study or who recently graduated from a top university, ideally focused on Computer Science or a Quantitative Degree.
  • Initial work experience in renowned firms in Technology, Data, Analytics or Consultancy is mandatory.
  • Proficiency using AI, LLMs or other data science approaches and Python coding skills.
  • Ability to complete projects on time and accurately, and to multi-task.
  • Strong analytical and people skills with excellent attention to detail and a strong desire to learn and succeed.
  • Proficiency in English is required.

What we offer

  • Insights into and learnings into the data and analytics space from the world of investments at one of the world's leading private markets investment firms.
  • Flat management structure with significant exposure to senior leaders and decision makers.
  • Steep personal and technical learning curve in a supporting environment with a high degree of ownership and autonomy, yet with structured feedback and training.
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