Senior Machine Learning Engineer

Key Skills

Analytical and Problem solving, Apache Kafka, JavaScript, Linux Operating system, MLOps tools, Natural Language Processing (NLP), NoSQL, Pandas, REST API, SQL

Job Description

If you are looking to enrich and enhance your Machine Learning experience on vast repository of data and knowledge that we possess, this is the place to be! Swiss Re is a risk knowledge company. Our work is about predicting, preparing and protecting against the world's biggest risks so society becomes stronger. The Digital & Technology department (D&T Re) is globally responsible for delivering solutions building and running our business. We are diverse team of experts who are passionate in providing innovative solutions for our reinsurance business. We are currently investing in building strategic data management capabilities to ingest and harness key data sets across prioritized business blocks especially in the area of Property & Casualty (P&C). We are looking for people with the right skills and passion to be part of our innovative journey!

Your key responsibilities:

• Lead projects with internal clients, plan tasks, timelines, communicate results and potential risks to customers.

• Become responsible for keeping existing solutions up and running efficiently. End-to-end.

• Implement new analytics solutions by building data ingestion and transformation pipelines, ML model training pipelines and orchestration on platforms.

• Participate in agile ceremonies such as defining team-internal objectives and key results, or project-specific Scrum events like sprint planning, backlog refinement, review, and retrospective sessions.

• Assess new and promising technologies with regards to their business potential and technical maturity, particularly in AI, MLOps, NLP and Generative AI.

• Use data from several data sources to extract features, train and test models, and rollout these models

• Design and implement data products in collaboration with data users and other engineering teams.

• Ensure reliability, quality, and optimal performance of our data products.

• Verify that the solution meets the business, compliance, and technical requirements.

About you

• A Bachelor/master's degree in computer science, data science, computer engineering or an equivalent experience

• Significant experience in code development/architecture experience in (Re)insurance industry. Experience in Property & Casualty (Re)insurance is an advantage.

• Working knowledge of machine learning, statistics, and natural language processing

• Proven ability with Data Validations/Transformation/Enrichments using python. Hands on python core, along with modules like pandas, regex, requests is a must.

• Experience using IDE like PyCharm/Visual Code

• Good knowledge of software engineering principles (e.g., IT security, REST APIs, OOP, entity-relationship models, data structures, algorithms etc.)

• The ability to work independently as well as part of a team.

• Good problem-solving skills

• Excellent communication abilities

The minimum gross monthly base salary for this role is 3300 EUR full time. Our final offer to you will be set up fairly, considering the skills and experience that you bring to the Swiss Re Group. You can look forward to extra rewards and benefits including an attractive performance-based bonus.

We provide feedback to all candidates via email. If you have not heard back from us, please check your spam folder.

About Swiss Re

Swiss Re is one of the world’s leading providers of reinsurance, insurance and other forms of insurance-based risk transfer, working to make the world more resilient. We anticipate and manage a wide variety of risks, from natural catastrophes and climate change to cybercrime. Combining experience with creative thinking and cutting-edge expertise, we create new opportunities and solutions for our clients. This is possible thanks to the collaboration of more than 14,000 employees across the world.

Our success depends on our ability to build an inclusive culture encouraging fresh perspectives and innovative thinking. We embrace a workplace where everyone has equal opportunities to thrive and develop professionally regardless of their age, gender, race, ethnicity, gender identity and/or expression, sexual orientation, physical or mental ability, skillset, thought or other characteristics. In our inclusive and flexible environment everyone can bring their authentic selves to work and their passion for sustainability.