Job Description

Our client is a successful large German company with more than 10,000 employees world-wide. Since 80 years the company has been making sense of large amounts of data from a wide variety of data sources with the aim to turn data into smart business decisions for their clients (Big Data). At the core of it, their Global Data Science team consists of more than 30 Data Scientist from all around the world. For this team we are currently looking for a

Big Data Scientist (m/f/d)

Python, PySpark, Hadoop

Your responsibilities:

  • As a Data Scientist (m/f/d), you will be part of a cross-functional development team, providing guidance and vision to other data scientists, and working hands-on with machine learning engineers, developers and client solution experts on delivering end-2-end analytic solutions for clients from the Technology industry
  • Develop offerings with an agile mindset, which requires you to actively contribute to all phases of the solution development. It will be your responsibility to translate the product vision into data/analytic/algorithmic requirements, to conduct PoCs and to build prototypes, and at a later stage to work on high-performance implementations.
  • Design and develop analytical approaches based on product concepts, going all the way from feasibility checks to proof-of-concepts to prototypes to implementation in end-to-end solutions
  • Work on Data Science projects, i.e. defining user stories and specific tasks working closely with Seniors, Product Owners and Product Managers
  • Closely collaborate with machine learning engineers/ software engineers on creating data-driven end-to-end solutions for marketers
  • Actively share Data Science knowledge within the team
  • Acting as strategic partner to the clients
  • Designing and project-managing data analytics solutions in complex project setups
  • Collaborating in cross-functional teams with experts in Sales, Operations Data and Marketing Science as well as in Product Management
  • Contributing to the financial success by co-owning the project P&L
  • Delivering insightful and actionable recommendations to the clients
  • Working together with Data Analysts, Marketing and Sales Managers from leading Technology & Durables companies in a dynamic and international environment

 

Your Profile:

  • PhD or Master degree that reflects strong modeling, statistics and IT skills.
  • Solid knowledge of Python programming, including pySpark
  • Solid skills with regard to working in Big Data environments (e.g., Cloudera Hadoop, Hortonworks Data Platform, AWS EMR, Map/Reduce, Hive)
  • Knowledge of the constantly evolving Data Science ecosystem and its frameworks (e.g., Hadoop, Spark MLlib, H2O, Tensorflow, Torch, Theano)
  • Basic skills with regard to performance optimization and scalability (e.g., parallelization, code optimization, containerization, function as a service)
  • Strong skills with regard to database handling, in particular SQL, NoSQL
  • Strong statistical modeling skills
  • Strong knowledge of optimization and / or machine learning algorithms and / or deep learning algorithms
  • Solid understanding of Big Data Architectures
  • Experience in agile Scrum teams, ideally experienced with SAFe

The offer:

 

  • Permanent role with a top employer that offers very good development possibilities  
  • Attractive salary and very good social benefits
  • International work environment
  • Help with relocation and if need Visa sponsorship available
  • Work with the latest, state-of-the art technologies and with interesting subject matters.   

  

Please use our online-application form only for applying to advertised position. Please note that we can´t consider applications that we receive by e-mail.

Do you have any questions or require further information? We are always happy to answer any enquires you may have either by telephone or by e-mail:

ANTAL INTERNATIONAL PERSONALBERATUNG

Andreas Dürr, E-Mail: aduerr@antal.com, Tel.: 0911 590 596 44

 
Get Jobs Like This By Email

Contact

Andreas Dürr
+49 911 590 596-44
 
×