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Serviceware is a leading provider of software solutions that enable the digitization of service processes. We have been listed on the stock market since 2018 and follow an ambitious growth strategy.
In 2019, we started an innovation center focusing on Artificial Intelligence (AI) and Machine Learning (ML). Serviceware AI was born! Using this initiative, we pursue three ideas:
- We seek to create an environment that allows fast experimentation and iteration. Few heavy processes. Freedom for creative ideas. Like a start-up within a publicly-traded company.
- We aim at developing ML features that are ready for production. Proof of concepts are nice, but we want our work to impact reality soon. This is why we envision software engineering and data science to be tightly linked right from the start.
- We like to take advantage of the recent progress in ML. Leverage the latest research insights. Cooperate with the technical university. Invest time in evaluating new technologies.
By now, we began to work on the first use cases related to Serviceware’s key expertise: service management. But which questions do we deal with in service management?
In short, that’s everything that improves today’s customer service by the analysis of data. For instance:
- How can we help businesses answering customer questions more quickly and reliably? (Advanced language models?)
- How can we enable companies to predict the costs of their customer services more accurately? (Time series analysis?)
- How can we support employees in finding knowledge needed for customer service more easily? (Neural networks?)
To build services that address these questions, we are hiring a (Senior) Data Scientist. And this is how your job looks like:
- You build state-of-the-art machine learning models to improve our software platform.
- You make sense of large data sets by conducting end-to-end analyses including data preparation, model training, and model evaluation.
- You choose suitable analytical approaches to effectively work on different business cases.
- You build on modern big data infrastructures to create scalable solutions.
- You are part of an agile software development team in Darmstadt.
- You intensively cooperate with our software engineers to facilitate a seamless integration of your machine learning models into the software.
What you bring to the table:
- Deep interest in data science and the development of machine learning models.
- Master's degree or Ph.D. in computer science, mathematics, statistics or a related field.
- Exceptional analytical skills and sound knowledge of current machine learning approaches.
- Strong experience with Python and common machine learning tools.
- Good knowledge of software engineering and database fundamentals.
- Willingness to contribute to continuous knowledge exchange and team learning.
- Effective communication skills (fluent in English).
Your future with us:
- You will work on a modern tech stack (Python, Scikit-learn, Pandas, NumPy, Spacy, Docker, Git, Postgres, Flask, Azure DevOps, SonarQube, …).
- You will possess a high degree of autonomy to pursue new ideas.
- You will have many options to improve your skills (e.g., by attending our coding conventions, conferences, or knowledge sharing session with the TU Darmstadt).
- You will have a true impact on our service management platform affecting thousands of individuals every day.
- You will work in our new office centrally located in the beautiful city of Darmstadt.
- You will be part of our international team of ML enthusiasts who are not only great at work but also love cooking, eating cake, going to the gym, watching Netflix, and playing the guitar.
How to Apply
Are you thrilled to join the team?! We can’t wait to read your application. Please consider the following guidelines when applying at Serviceware AI:
- Applications are possible in English as well as in German.
- We expect you to write a short cover letter that tells us why you like to work at Serviceware AI. (Please don’t use stock cover letters. We’d love to hear why you like this particular job.)
- While we enjoy reading about your experiences, please keep your CV focused on the main points. We are not looking for CVs with more than two to three pages.