ML Engineer (Forecasting) | NDA
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a ML Engineer (Forecasting) | NDA in Germany.
This role offers the opportunity to work on high-impact forecasting systems that directly influence operational efficiency within a large healthcare environment. You will design and deploy machine learning models that predict demand, optimize staffing, and improve resource allocation across clinical and marketing operations. Working in a fast-paced, project-driven setting, you will contribute to building scalable, production-ready ML solutions from early discovery through to deployment. The position involves close collaboration with data, product, and cloud engineering teams to transform complex healthcare datasets into actionable insights. With a strong focus on time-series forecasting and applied machine learning, you will help shape data-driven decision-making processes that have real-world impact. This is an excellent opportunity for an ML engineer who enjoys end-to-end ownership, applied research, and building production-grade forecasting systems.
Accountabilities:
- Design, develop, and deploy machine learning models focused on time-series forecasting and demand prediction use cases.
- Build scalable data pipelines and ML workflows using cloud platforms such as AWS, GCP, or Azure.
- Develop and optimize forecasting models including ARIMA/SARIMA, Prophet, LSTM, and other advanced predictive approaches.
- Perform data preprocessing, feature engineering, and exploratory analysis on complex healthcare and operational datasets.
- Collaborate with cross-functional teams including data engineers, product managers, and cloud specialists to deliver robust solutions.
- Participate in the full project lifecycle, from problem definition and proof of concept through to production deployment and stakeholder presentation.
- Ensure model reliability, scalability, and performance in production environments.
- Continuously evaluate and improve forecasting accuracy using appropriate metrics and validation techniques.
Requirements:
- 4+ years of experience in Machine Learning, Data Science, or applied AI roles.
- Strong expertise in time-series forecasting techniques and models such as ARIMA, Prophet, LSTM, or equivalent approaches.
- Advanced Python programming skills with experience using libraries such as Pandas, NumPy, scikit-learn, and PyTorch.
- Hands-on experience deploying machine learning models into production environments.
- Solid understanding of data preprocessing, feature engineering, and statistical modeling for time-series data.
- Experience working with cloud platforms such as AWS, GCP, or Azure.
- Strong knowledge of SQL and version control systems such as Git.
- Ability to work independently in ambiguous environments with strong problem-solving and analytical thinking skills.
- Excellent communication skills with the ability to explain technical concepts to both technical and non-technical stakeholders.
- Advanced English proficiency required.
Benefits:
- Competitive contract-based compensation aligned with experience and project scope.
- Fully remote working arrangement across Europe, including the United Kingdom.
- Opportunity to work on real-world healthcare forecasting systems with measurable operational impact.
- Exposure to end-to-end machine learning lifecycle, from research to production deployment.
- Collaboration with experienced engineers and data professionals in a high-impact environment.
- Hands-on experience with modern ML stacks and cloud-native technologies.
- Flexible engagement structure with potential for extension beyond the initial project duration.
- Opportunity to contribute to meaningful AI applications in healthcare and operations optimization.
