5 months ago
Frankfurt, GermanyEntry Level
Responsibilities
- Develop and implement machine and deep learning solutions for time-series forecasting, tabular machine learning, and causal inference.
- Support end-to-end client projects involving demand forecasting, pricing, anomaly detection, and predictive maintenance.
- Design, implement, validate, and deploy models using statistical, machine learning, and deep learning methods.
- Apply controlled experiments, uncertainty quantification, causal analysis, and decision optimization to business problems.
- Help build robust, scalable, and maintainable ML pipelines and deploy models on Azure, AWS, or GCP.
- Collaborate with clients, stakeholders, consultants, data scientists, and engineers across industries and use cases.
- Gradually take responsibility for project work packages, contribute to proposals, and support internal forecasting best practices.
Requirements
- Completed bachelor’s or master’s degree in a quantitative field such as data science, statistics, mathematics, economics, computer science, business informatics, or a comparable subject.
- Initial practical data science experience through internships, working-student roles, or one to three years of relevant professional experience.
- Very strong Python skills and confidence using modern tools and libraries for data analysis, machine learning, and software development.
- Solid knowledge of machine learning and statistics, including model validation, interpretation, causal analysis, and deriving business insights.
- Initial experience with time-series forecasting using methods such as ARIMA, ETS, LightGBM, XGBoost, N-BEATSx, N-HiTS, TFT, or PatchTST.
- Interest in applying forecasting, anomaly detection, and decision optimization in probabilistic and causal contexts.
- Experience with time-series foundation models such as TimesFM, Chronos, or Moirai is advantageous.
- Ideally, initial experience with cloud platforms, MLOps concepts, or deploying models into production environments.
- German proficiency of at least B2 and excellent English proficiency at C1 level or higher.
- Structured, curious, proactive working style and motivation to develop in a consulting environment.
- Willingness to make occasional customer-site trips in Germany, Austria, and Switzerland.
Benefits
- Work on varied and challenging Data & AI projects for well-known clients across industries.
- Professional development through regular feedback, individual support, training opportunities, and a mentoring program.
- Open, diverse, respectful work environment with flat hierarchies, short decision paths, and strong team collaboration.
- Iterative and modern working culture with clear communication, autonomy, and room for new ideas.
- Fair, structured, and transparent salary bands adjusted regularly to market and performance developments.
- Primarily based at the modern Frankfurt office, with regular remote work and up to four weeks per year working remotely from another EU country.
- Discounted Deutschlandticket and reduced-cost access to sports and wellness services through Wellpass.
- High-quality IT equipment such as a MacBook Pro, regular team events, childcare subsidies, and employee discounts.