We offer ambitious talents the opportunity to contribute and further develop their expertise in the position of Senior / Principal Data Scientist (m/f/d).
Here's what we offer
1. Attractive salary and long-term job security through affiliation with the Group
2. Up to 30 days vacation per year
3. Contribution to company pension scheme after end of probationary period
4. Extensive social benefits, including Christmas and vacation bonuses
5. Compensation for travel expenses
6. Usually a permanent employment contract
7. Good chances of being taken on by our business partners
8. Targeted training opportunities and free language courses
9. A wide range of discounts for employees
Your tasks
Data Analysis & Modeling:
- collect, clean, and preprocess structured and unstructured data from various sources
- perform exploratory data analysis to uncover trends and patterns
- dvelop predictive and prescriptive models using machine learning and statistical techniques
Algorithm Development:
- design, develop, customize, optimize, and fine-tune algorithms tailored to specific use cases such as anomaly detection, predictive modeling, time-series forecasting, recommendation systems, text generation, summarization, information extraction, chatbots, AI agents, code generation, document analysis, sentiment analysis, data analysis, etc.
Application Development:
- collaborate with developers and stakeholders to integrate statistical models, LLMs and classical AI techniques into end-user applications, focusing on user experience, and real-time performance
End-to-End Pipeline Development:
- build and maintain production-ready end-to-end pipelines, including data ingestion, preprocessing, training, evaluation, deployment, and monitoring
- automate workflows using DevOps / MLOps best practices to ensure scalability and efficiency
Scalable Model Deployment:
- collaborate with other developers to deploy models at scale, using cloud-based infrastructure (AWS, Azure)
Monitoring and Maintenance:
- implement continuous monitoring and refining strategies for deployed models, using feedback loops and e.g. incremental fine-tuning to ensure ongoing accuracy and reliability; address drifts and biases as they arise.
Your profile
- ideally Master's degree in data science, computer science, statistics, or related quantitative field
- best 5+ years of experience in data science or a related role
- perfect would be 2+ years of experience in AI/ML engineering, with exposure to both classical machine learning methods and language model-based applications
Technical Skills:
- advanced proficiency in Python, data analytics, statistical modeling and ML/AI. Experience with leading ML/AI frameworks and tools, with hands-on experience in designing and implementing end-to-end GenAI pipelines
DevOps / MLOps Knowledge:
- strong understanding of DevOps / MLOps tools and practices, including version control, CI/CD pipelines, containerization, orchestration, infrastructure as code, automated deployment
Deployment:
- experience in deploying statistical models, LLM and other AI models with cloud platforms (AWS, Azure) for robust and scalable productizations
Data Engineering:
- expertise in working with structured and unstructured data, including data cleaning, feature engineering with data stores like vector, relational, NoSQL databases and data lakes through APIs
Transferable Skills:
- effective communication in English, problem-solving and innovative mindset, adaptability, curiosity, responsibility