CEPRES
is
the leading and fastest growing digital investment platform for private capital
markets, an institutional asset class which became very relevant in global
investment portfolios of sovereign wealth funds, insurances, pension plans and
others. This global institutional client base benefits from our award-winning
investment solutions for their investment activities while we connect via the
CEPRES platform thousands of professionals to the largest private investment
network worldwide.

CEPRES
GmbH / Corp
is headquartered in Munich and New York, with additional offices
in Denver, Heidelberg, and several locations in the Middle East. Our team is
incredibly diverse with over 20 nationalities globally. We value smart and
innovative people who also work effectively in a team environment and who are
global players.

We are seeking a
Data
Scientist Associate / Senior Associate
to help drive CEPRES' next
generation of data, analytics, and AI capabilities.

This role is ideal for candidates
who enjoy solving complex data challenges and developing practical solutions
that improve the quality, scalability, and accessibility of private markets
data. You will work at the intersection of finance, data science, and
technology, building analytical models, intelligent automation solutions, and
innovative tools that support both client-facing products and internal
operations.

1. 
   Data Science & Advanced Analytics

• 
  Develop scalable data science and analytics solutions for large private markets datasets.
• 
  Design methodologies to extract, validate, enrich, and standardize investment data from structured and unstructured sources.
• 
  Apply statistical, machine learning, and AI-driven techniques to improve data quality and operational efficiency.
• 
  Support the development of analytical frameworks, data models, and business insights.

2. 
   AI & Innovation

• 
  Develop intelligent workflows leveraging modern AI technologies, including LLMs and automation frameworks.
• 
  Contribute to CEPRES’ AI and data strategy by identifying practical use cases and opportunities for innovation.
• 
  Evaluate emerging technologies and support their adoption across the organization.
• 
  Partner with business stakeholders to translate complex challenges into scalable solutions.

3. 
   Data Engineering & Automation

• 
  Build and maintain data pipelines, automation frameworks, and quality control mechanisms.
• 
  Query and analyze large datasets using SQL and Python.
• 
  Collaborate closely with Engineering, Product, and Operations teams to improve data processing and platform capabilities.
• 
  Document methodologies, processes, and best practices to support scalable implementation.

4. 
   Leadership & Collaboration (Senior Associate)

• 
  Lead analytical work streams and innovation initiatives.
• 
  Mentor junior team members and contribute to capability development.
• 
  Drive continuous improvement across data science, automation, and analytical processes.

Requirements

Benefits