Senior Data Scientist (Statistics & ML Expert)

Job title: Senior Data Scientist (Statistics & ML Expert)

Company: Red Bull


Job description: If you know the difference between correlation & causation, have an excellent understanding of classical probability & statistics as well as state of the art ML algorithms and want to drive real business impact at one of the most recognisable brands globally, this job is for you!Ihre AufgabenIn this role, you’ll contribute to global Data Science projects to enable stakeholders to make better data-driven decisions. As a Statistics & ML Expert you’ll be responsible for the methodological aspects of Data Science projects in fields like statistical forecasting, network optimisation, quality assurance, sports analytics, and others. You know how and you know why specific Data Science methods & algorithms should be applied and you know how to develop new ones. Always aiming for highest quality results, you are also able to come up with pragmatic solutions if the situation demands it.Your focus is not only on delivering (model) outputs, but you are also able to explain and present your results to both, a technical and non-technical audience. As a team player you’ll support the team and the organisation with your expert knowledge.Areas that play to your strengthsAll the responsibilities we’ll trust you with:

  • You’ll support the team by efficiently managing, running, and delivering Data Science projects. This end-to-end approach includes everything from project scoping, execution, quality assurance, and delivery via convincing presentations.
  • Not content focusing exclusively on existing service lines and initiatives, you will actively think along and propose new ways of generating even more value for our stakeholders.
  • You’ll build close relationships with internal and external stakeholders. Thanks to your collaborative attitude and ability to absorb constructive feedback, you will maximise the likelihood of making each and every Data Science initiative a success for the company.
  • You’ll work inside the Data Science Team and you’ll support them with impact tracking, project and pipeline planning, preparing materials for the planning cycles, internal trainings, onboarding new colleagues, internal and external outreach.

Ihr Profilthat matter most for this role:

  • 4+ years of experience in Data Science. Previous experience working as a Machine Learning Expert is a plus
  • Masters or Doctorate in relevant field, for instance: Mathematics, Statistics, Science (including data, behavioural, social, econ, …)
  • Good command of English, both spoken and written. German a plus
  • Programming: know at least one of R, Python, SQL with the ability and willingness to learn the other two
  • Data Literacy: ability to prepare datasets ensuring top quality such that essence of said data and the implications for the problem at hand can be grasped quickly
  • Statistical Reasoning: theoretical and applied understanding of Stats, Probability and ML Algorithms and know how to use these tools to reduce uncertainty in a business context (regression, visualization)
  • Technical Literacy: applied understanding of modern computing allows the candidate to do things which go beyond the strict definition of Data Science (git, API calls, web crawling, …)
  • Presentation Skills: present coherent data stories at the appropriate level of abstraction given the audience
  • Stakeholder Management: skilled at building mutually beneficial connections with functional stakeholders
  • Pragmatic Critical Thinking: intuitively consider relevant costs/benefits in all decisions and act accordingly
  • Outcome Driven: highly motivated to add value and to demonstrate that impact to the organization
  • Scientific Reasoning/ Scoping: ability to define and formulate new questions, in addition to answering given ones
  • Grit: proven capability to see things through to the end even if initial feedback is discouraging

Travel 0-10%Wir bieten

Expected salary:

Location: Elsbethen, Salzburg

Job date: Fri, 16 May 2025 07:11:15 GMT

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