WAS SIE ERWARTET
- Design, Entwicklung und Dokumentation von Embedded Software auf Sicherheitssteuerungen
- Sicherstellung gleichbleibend hoher SW-Qualität und stetige Optimierung des Entwicklungsprozesses
- Planung und Umsetzung von automatisierten Tests auf verschiedenen Ebenen
- Leitung von Softwareentwicklungs-Projekten unter Einhaltung des entsprechenden Entwicklungsprozesses
- Entwicklung technischer Konzepte in Abstimmung mit interdisziplinären Experten
|
Was Sie erwartet
- Design, Entwicklung und Dokumentation von Embedded Software auf Sicherheitssteuerungen
- Sicherstellung gleichbleibend hoher SW-Qualität und stetige Optimierung des Entwicklungsprozesses
- Planung und Umsetzung von automatisierten Tests auf verschiedenen Ebenen
- Leitung von Softwareentwicklungs-Projekten unter Einhaltung des entsprechenden Entwicklungsprozesses
- Entwicklung technischer Konzepte in Abstimmung mit interdisziplinären Experten
|
Deine Aufgaben
- Planung, Entwicklung und Durchführung von Testfällen für Hard- und Firmware-Komponenten
- Aufbau und Pflege automatisierter Testsysteme und Testumgebungen
- Analyse und Dokumentation von Testergebnissen sowie Identifikation und Nachverfolgung von Fehlern
- Enge Zusammenarbeit mit der Entwicklungsabteilung zur kontinuierlichen Verbesserung von Qualität und Testabdeckung
- Unterstützung bei der Definition und Weiterentwicklung von Teststrategien und -prozessen
|
RESPONSIBILITIES
- 5+ years’ experience in media monitoring, sponsorship analysis, or related fields (agency background preferred).
- Strong analytical mindset with the ability to structure and interpret data (ETL) into actionable insights.
- Proven experience sourcing and evaluating earned media and monitoring data, with expertise in managing external suppliers or outsourced teams.
- Familiarity with social media platforms and analytics tools (e.g., Sprinklr, native reporting dashboards).
- Basic understanding of Python and motivation to grow technical skills.
- Proactive, adaptable, and curious, with a passion for sports, culture, and data storytelling.
|
Your responsibilities
- Design, implement and maintain data ingestion, transformation and provisioning
- Design data models and data architecture for effective data processing and storage
- DataOps: orchestrate and monitor data load processes, ensure data quality
- Support Machine Learning Operations (MLOps) with high-quality data products
- Create and maintain documentation
|
Die Rolle
- Aufbau von vertrauensvollen Beziehungen zu den Marketing-Teams und Unterstützung in allen finanziellen Angelegenheiten.
- Sparringspartner für Budgets, Forecasts und Ausgabenentscheidungen.
- Hinterfragen von Annahmen, Unterstützung von Entscheidungsfindungen und Förderung von Kostenbewusstsein.
- Lieferung von Ad-hoc-Analysen und Business-Insights, um Projekte mit hoher Wirkung zu unterstützen.
|
RESPONSIBILITIES
- Experience in FMCG, Business, or IT, with strong project management and problem-solving skills
- University Degree in Economics, Business Administration or similar or equal practical experience
- Excellent English skills, German is an advantage
- Analytical mindset with great attention to detail, structured thinking, and a process-driven approach
- Proficient in Microsoft Office; experience with BI tools or coding languages (e.g. Power BI, Tableau, Python, SQL) is a plus
- Strong communication, presentation, and organizational skills to clearly convey insights and solutions
- Self-motivated learner who works well independently and in teams
|
RESPONSIBILITIES
- 5+ years of experience in Data Science. Previous experience working on Data Science topics in Operations / Supply Chain is a plus.
- Programming: proficient in 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.
- 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, …).
- Statistical Reasoning: applied understanding of Stats and Probability and know how to use these tools to reduce uncertainty in a business context (regression, visualisation).
- Project Management: able to navigate evolving requirements, prioritise effectively, and scope work in a way that balances impact, effort, and stakeholder needs.
- 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 organisation.
- 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.
|
RESPONSIBILITIES
- Minimum of 3 years of professional experience as an Operations or Logistics Controller
- Degree in Business Administration with a focus on Finance/Controlling/Logistics/Supply Chain Management
- Excellent knowledge in English
- Experience in the area of cost-type and cost-unit controlling
- Excellent analytical, communication, problem solving and stakeholder management skills
- Experience with SAP ERP (FI/CO, SD), SAP TM, SAP BI, and Oracle Hyperion is beneficial
- Good command of advanced analytics and data visualization tools (Python, R, PowerBI, Tableau) is a plus
- Analytics mindset, Future vision focus, and passion for working with numbers
- Accuracy, reliability, flexibility, and result orientation
- Proactive, self-motivated, self-reliant and able to work under pressure in a fast-paced team environment
|
RESPONSIBILITIES
- 4+ years of experience in Data Science. Previous experience working on Data Science topics in Operations / Supply Chain is a plus.
- Masters or Doctorate in relevant field, for instance: Mathematics, Operations Research, Science (including data, computer, behavioural, social, e-con, ...).
- 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
|
RESPONSIBILITIES
- Minimum of 2-3 years of professional experience as a data professional (e.g. data engineer, data scientist) or in a business/IT consulting position
- Strong and proven knowledge in SQL and database cloud solutions, ideally Snowflake, combined with proficiency in standard data architecture design and modelling.
- Expertise in using Python and Git/Github is expected; familiarity with PySpark and Snowpark will be a strong plus
- Experience in creating interactive web apps (e.g., using Streamlit or RShiny) and knowledge of business intelligence tools like Tableau and Power BI are beneficial
- Strong communication and presentation skills.
- Team-player and collaborative (“copy-left” vs “copyright”).
- Proactive, self-motivated, and able to work on different projects in parallel.
|
RESPONSIBILITIES
- Experience in user research and talking to stakeholders to bridge the gap between the problem of a user and actual AI implementation options
- Proven experience in developing AI-powered solutions, from research to production-ready implementation.
- Strong foundation in modern AI/ML frameworks, patterns and tooling, especially in Generative AI, covering concepts like prompt engineering, RAG, LLM as a judge, fine-tuning, and so on.
- Familiarity with cloud platforms (preferrable AWS) and LLMOps & MLOps pipelines for deploying and scaling AI solutions.
- Expertise in model optimization and evaluation techniques to build robust AI workflows.
- Solid skills in Python (or other relevant languages) and practical experience in applying modern software engineering patterns (like version control systems, merge requests, pair-/mob-programming, testing)
- Strong interest and basic knowledge about Agentic AI and agentic architectures
- Strong communication skills, able to explain technical solutions to non-technical audiences.
- Excellent problem-solving and analytical skills, with a proactive approach to challenges.
- Ability to work collaboratively with cross-functional teams.
- Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines
- Enjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done
- Affinity for media and broadcast domain is a plus
|
