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Data Scientist (all genders)
Munich, Bavaria, Germany · Full Time
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- Experience
- 3+ yrs
- Salary
- —
- Openings
- 1
- Posted
- 1 week ago
- Work mode
- In office
- Education
- Data Science, Statistics, Mathematics, Computer Science, Business Informatics, or comparable qualification
- Eligibility
- Candidates with a completed degree or comparable qualification in a quantitative, analytical, or business-related discipline, along with several years of relevant data science or marketing analytics experience and strong English and German communication skills, are eligible to apply.
- Resume
- Required to apply
Where you'll work
Job description
Role Overview
THE MARCOM ENGINE, part of the Serviceplan Group, is hiring a Data Scientist in Munich to start as soon as possible on a full-time basis. You will join a cross-functional team that connects data science, strategy, and automation, contributing to digital transformation projects for well-known global brands. The role focuses on consumer insights, personalization, and data-driven marketing measurement.
What You Will Do
- Build and deploy machine learning models and related algorithms.
- Explore datasets to uncover trends, patterns, and actionable findings.
- Support initiatives involving data and processing for AI agents.
- Collaborate with internal teams and client contacts to develop practical, data-backed solutions.
- Test and validate models, then interpret outcomes through statistical techniques and hypothesis testing.
- Keep up with current methods and developments in data science and analytics.
- Maintain clear documentation for models, processes, and related work.
- Use automation and machine learning to speed up analysis and increase insight delivery.
- Design advanced analytical models that show how marketing drives business growth, including media effectiveness and customer lifetime value.
- Contribute in a multidisciplinary environment focused on improving measurement and optimization across marketing, strategy, and automation.
What We’re Looking For
- A completed degree in a quantitative, analytical, or business-focused discipline such as Data Science, Statistics, Mathematics, Computer Science, or Business Informatics, or an equivalent qualification.
- Multiple years of experience working as a Data Scientist or Marketing Analyst, ideally with a strong emphasis on statistical modeling and marketing analytics, preferably in an agency or fast-moving environment.
- Strong Python expertise, including familiarity with relevant libraries.
- Solid capability in writing and working with queries and comfort handling different data formats and systems such as SQL, Redshift, and PostgreSQL.
- Practical experience using machine learning and automation to streamline analytical tasks.
- Exposure to cloud platforms such as GCP, AWS, or Azure, plus dashboarding and visualization tools like Quicksight, Tableau, Power BI, or Looker.
- Ability to turn complex statistical results into clear, strategic recommendations.
- Experience with digital analytics tools or marketing campaign datasets.
- Very good communication skills in both English and German.
- A curious, proactive, and cooperative working style.
- Awareness of information security principles and related best practices.
What We Offer
- A structured onboarding experience, including a welcome session, digital onboarding day, newcomer coffee, and a newcomer introduction round.
- Access to learning and development through internal campus training, optional language courses, and regular coaching.
- Flexible work arrangements, including adaptable working hours, mobile office options, and job-sharing models.
- A lively workplace culture with after-work events and company-supported fitness programs.
- A modern office located in Munich’s creative district with convenient access.
- An international environment with opportunities to connect and exchange ideas across disciplines and locations worldwide.
Additional Information
This is a full-time, onsite position based in Munich, Bavaria, Germany. The role is available at the earliest possible start date.