Sr Data Scientist

vor 1 Tag

Munich, Bayern, Deutschland Workster Jobs Vollzeit 80.000 € - 120.000 € pro Jahr


Workster is excited to be recruiting for an experienced Senior Data Scientist – Causal Inference to join a forward-thinking technology leader based in Munich, Germany. This is your opportunity to contribute to innovative, data-driven decision making within a high-impact, international team shaping the future of B2B solutions.

Key Responsibilities – Senior Data Scientist Causal Inference Jobs in Munich
  • Lead end-to-end causal inference projects to assess business strategies, interventions, and product enhancements in a real-world environment.
  • Design robust experiments including A/B tests, quasi-experimental methods, and observational studies, ensuring polices are guided by solid statistical evidence.
  • Apply advanced statistical, econometric, and machine learning techniques to uncover insights about causality and drive actionable recommendations.
  • Collaborate cross-functionally with Data Engineering, Product, and Business stakeholders to translate complex data challenges into clear, impactful solutions.
  • Mentor and upskill team members in state-of-the-art approaches to causal modelling, fostering a culture of continuous learning and excellence.
  • Communicate findings persuasively to both technical and non-technical audiences, supporting data-driven strategy at every organisational level.
  • Stay at the forefront of developments in causal inference, data science, and AI, and evaluate opportunities to introduce novel methodologies or tools.
Requirements and Qualifications – Causal Inference Data Scientist Career Munich
  • Master's degree or PhD in Statistics, Computer Science, Mathematics, Econometrics, or a closely related discipline.
  • Substantial experience applying causal inference techniques (e.g. propensity score matching, difference-in-differences, instrumental variables, regression discontinuity, randomised controlled trials) in a commercial or research context.
  • Solid programming skills in Python and/or R, with proficiency in relevant libraries such as pandas, statsmodels, scikit-learn, or PyMC.
  • Demonstrated ability to work with large, complex datasets using SQL and contemporary data platforms.
  • Excellent written and verbal English communication skills – German language knowledge is an asset but not essential.
  • Strong stakeholder engagement abilities, adept at translating data insights into business value and operational impact.
  • A proactive, collaborative mindset and a commitment to promoting diversity, equity, and inclusion in all team interactions.
Benefits – Senior Data Scientist Opportunities in Germany
  • Competitive and transparent salary structure, with performance-linked bonuses.
  • Relocation support and visa sponsorship for eligible candidates moving to Munich.
  • Flexible working arrangements, including hybrid and remote options.
  • Comprehensive private health insurance and wellness initiatives.
  • Generous annual leave, learning budget, and access to professional development resources.
  • Dynamic and welcoming working culture, celebrating innovation, autonomy, and teamwork.
  • Modern, well-located office in the heart of Munich, with excellent public transport connections.
Why Build Your Career in Data Science with Causal Inference in Munich?
  • Drive real-world impact as you enable evidence-based decisions across pioneering B2B products and services.
  • Collaborate with talented international colleagues at the leading edge of data science and AI.
  • Enjoy Munich's vibrant, multicultural environment and exceptional quality of life while progressing your career.
  • Join an organisation committed to sustainability, diversity, and continuous advancement in all aspects of business and technology.
Next Steps – Apply for Senior Data Scientist Causal Inference Jobs in Munich

If you are passionate about causal inference, eager to solve complex challenges, and ready to make your mark in a diverse, high-growth company, apply now to join our team in Munich

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