Data Science & Analytics

It's all about data

The Big Data market continues to exhibit strong momentum as businesses accelerate their transformation into data-driven companies.

Data analysis, descriptive statistics and predictions about future events, linear optimization, but also the development of AI (Artificial Intelligence) are important core components of this field. However, data science also requires deep knowledge of relational databases and Structured Query Language (SQL).

We find candidates who have been dealing with this topic for many years in order to make their company future-proof through applied science.

Typical roles

Head of Data Science / Quant Developers / Data scientists / DevOps Developers / Big Data engineers / Machine learning scientists / Business analytics specialists / Data visualization developers / Data Analysts / BI solutions architects / Senior Manager Data Science & Analytics / Development Engineer Data Science and Analytics / Senior IT Project Managers Data Science

Technologies involved

Angoss, AWS Analytics, Elastic, Alteryx, IBM Predictive, Analytics, BeyondCore, Oracle Data Mining, Revolution Analytics, Salford, Systems, Pervasive, Hadoop, Tableau, SAS Analytics, Statistica,Tibco Analytics Software, KXEN

Jobs in Data Science & Analytics

Tech News

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Infographic: The Data Scientist Shortage

The supply of information stored digitally and accessible to web users worldwide currently amounts to around 4.4 Zettabytes or 4.4 Trillion Gigabytes. Of that information, most of it was produced in the last 2 years; more than has been produced since the beginning of recorded information from worldwide civilizations. Statistics like these point to a promising career in data science for anyone with the skills and interest to pursue this field in the 21st Century.
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Feb

Doing "Good" Data Science

Data scientists, data engineers, AI and ML developers, and other data professionals need to live ethical values, not just talk about them.
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15
Nov

Essential skills and traits of elite data scientists

These days the data scientist is king. But extracting true business value from data requires a unique combination of technical skills, mathematical know-how, storytelling, and intuition.
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