Data Scientist at Hays Professional Solutions GmbH Standort Ingolstadt
berlin, Berlin, Germany -
Full Time


Start Date

Immediate

Expiry Date

09 Dec, 26

Salary

44000.0

Posted On

17 Sep, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Industry

Banking & Credit

Description

We are looking for a future Data Scientist (m/f/d) in the Advanced Analytics area of ​​the Analytics, Data & AI department.

As a Data Scientist (m/f/d), you will work at the interface between data, technology, and business. You will analyze complex datasets, develop models to predict behavior and outcomes, and support data-driven decisions in various business areas – from marketing and sales to operations.

  • Analysis of large, structured and unstructured datasets from various sources (e.g., CRM systems, web analytics, internal databases, external APIs)
  • Development and application of machine learning algorithms and statistical models for the prediction, classification, and optimization of business processes.
  • Creation of dashboards, reports, and interactive visualizations to support data-driven
  • Decisions – for departments and management
  • Use of modern tools and technologies: from Python (e.g., scikit-learn, pandas, XGBoost, TensorFlow/Keras, PyTorch) to R (e.g., tidyverse, shiny) to SQL and Power BI
  • Continuous development of your skills – through training, your own research, open-source contributions and

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Responsibilities

We are looking for a future Data Scientist (m/f/d) in the Advanced Analytics area of ​​the Analytics, Data & AI department.

As a Data Scientist (m/f/d), you will work at the interface between data, technology, and business. You will analyze complex datasets, develop models to predict behavior and outcomes, and support data-driven decisions in various business areas – from marketing and sales to operations.

  • Analysis of large, structured and unstructured datasets from various sources (e.g., CRM systems, web analytics, internal databases, external APIs)
  • Development and application of machine learning algorithms and statistical models for the prediction, classification, and optimization of business processes.
  • Creation of dashboards, reports, and interactive visualizations to support data-driven
  • Decisions – for departments and management
  • Use of modern tools and technologies: from Python (e.g., scikit-learn, pandas, XGBoost, TensorFlow/Keras, PyTorch) to R (e.g., tidyverse, shiny) to SQL and Power BI
  • Continuous development of your skills – through training, your own research, open-source contributions and


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