Machine Learning Engineer

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

About the role

Located within Swiss Re's Group Data Services (GDS) department the Predictive Analytics Solutions team consists equally of data scientists and software engineers. We have several years' worth of experience building and hosting machine learning models, predictive analytics and big data solutions in a production environment end to end. Typically, what we build we also maintain. Currently, we are interested particularly in the adoption of standards and methodologies around MLOps and Responsible AI, for example data and model drift monitoring, model explainability or synthetic dataset generation. Does that sound interesting?

What will you achieve in the first 12 months after joining?

• Implement new analytics solutions by building data ingestion and transformation pipelines, ML model training pipelines, and dashboard solutions
• Become responsible for keeping existing solutions up and running smoothly. End-to-end.
• Help us to stay compliant with our company-wide governance processes and security requirements
• Participate in agile ceremonies such as defining team-internal OKRs, or project-specific Scrum events like sprint planning, backlog refinement, review and retrospective sessions.
• Assess new and promising technologies related to advanced analytics with regards to their business potential and technical maturity, particularly in the area of Responsible AI and MLOps.
• Communicate your findings to others within Swiss Re, thus contributing to the company-wide adoption of new technologies and knowledge.
• As your experience grows, you will take the lead in small analytics projects of up to roughly 4 members for SR internal clients. Together with the client you will plan milestones and deliverables, communicate regular updates to project sponsors and celebrate successes with the project team itself.

Technical skills:

• Strong Apache Spark skills (e.g. Spark SQL, PySpark and Spark ML)
• Very strong Python (e.g. scikit-learn, unittest) skills, intermediary Java and basic R skills
• Intermediary SQL skills
• Good knowledge of software engineering principles (e.g. IT security, JSON & REST APIs, OOP/OOD, FP, JDBC, entity-relationship-models, etc.)
• Willingness to learn Palantir Foundry
• Experience with Microsoft Azure/AWS/Alibaba cloud or similar cloud providers
• Basic knowledge of Docker
• Intermediary applied knowledge of machine learning, statistical analysis and predictive modelling
• Basic DevOps skills

What we expect from you:

• Batchelor, Master's or PhD degree in computer science, data science or equivalent
• 5+ years of professional experience developing software with an analytics focus
• Advanced understanding of the entire data science development lifecycle: idea inception, feature engineering, model training, packaging, deploying and hosting a model
• Understand a complex enterprise software landscape: big data and analytics platforms, MLOps
• Full professional proficiency in oral and written English