Data Scientist (Sales & Marketing Focus)
This role is ideal for a skilled Data Scientist who wants to drive real impact at a globally recognised brand.
You will contribute to global data science projects, enabling business stakeholders from various departments to make better data-driven decisions. The Data Scientist will work closely with other team members to build and run data products, apply statistical analyses to solve business problems, and create convincing presentations to demonstrate the impact to the wider organisation.
Key Responsibilities
* Deliver Projects: Manage, run, and deliver data science projects with a focus on sales, marketing, and HR stakeholders. This includes project scoping, execution, quality assurance, and delivery via presentations.
* Scale Initiatives: Work with IT colleagues to find efficiencies and scale initiatives to more people and Red Bull markets.
* Drive Innovation: Think along with existing service lines and propose new ways of generating value for stakeholders.
* Manage External Consultants: Guide external colleagues to deliver data science projects efficiently and ensure top-notch quality.
* Stakeholder Management: Build close relationships with internal and external stakeholders and maximise the likelihood of success for each data science initiative.
* Support the Data Science Manager: Assist with impact tracking, projects, pipeline planning, preparing materials for planning cycles, internal trainings, onboarding new colleagues, internal and external outreach, and more.
Requirements
1. Programming: Knowledge of Python, SQL, or R, with the ability and willingness to learn the others. Snowflake or Databricks knowledge is a plus.
2. FMCG Knowledge: Prior experience working in an FMCG company in a data or analytics focused role is a plus.
3. Data Literacy: Ability to prepare high-quality datasets ensuring the essence of the data and its implications can be quickly grasped.
4. Statistical Reasoning: Applied understanding of statistics and probability, and know-how to use these tools to reduce uncertainty in a business context.
5. Technical Literacy: Applied understanding of modern computing allows the candidate to do things beyond the strict definition of data science.
6. Presentation Skills: Present coherent data stories at the appropriate level of abstraction given the audience.
7. Stakeholder Management: Good at building mutually beneficial connections with functional stakeholders.
8. Pragmatic Critical Thinking: Intuitively consider relevant costs/benefits in all decisions and act accordingly.
9. Outcome Driven: Highly motivated to add value and demonstrate that impact to the organisation.
10. Scientific Reasoning/Scoping: Ability to define and formulate new questions, in addition to answering given ones.
11. Grit: Proven capability to see things through to the end even if initial feedback is discouraging.
12. Travel: 10-20% travel required.