Xomnia’s core team
We distinguish three different roles within our team to help you build an organisation that is ready for the future.
Our Analytics Translators are data driven business consultants. They support you by exploring potential data-driven opportunities, developing data strategies or leading their implementation. They manage teams of data scientists and engineers to deliver complex data products or solve other data driven challenges.
Xomnia’s Analytics Translators make sure that relevant stakeholders are aligned and possible impediments are mitigated. They understand business challenges, think strategic, but excel in their hands-on and get shit done mentality. Our Analytics Translators are fully focused on making impact with data and AI at your organisation.
Xomnia data engineers are specialised in taking on complex problems such as developing scalable data pipelines, designing and implementing cloud architectures, productionizing machine learning models and building custom software solutions. They follow and create the best practices in the field and ensure the right level of automation.
Our team of data engineers is experienced with all the different cloud environments (Azure, GCP, AWS). Each of them has strong software engineering skills in Python, Scala or Java and knowledge of software testing and CI/CD. They are aware of the latest, and through their vast experience with proven technologies such as Spark, Scala, Cassandra, Airflow, Kafka and Kubernetes they know how to use the right stack for the right problem. Xomnia data engineers are solution focused, and are trained not to overdesign.
With their technical and social skills, they easily connect to your internal team and everything is geared towards achieving goals together!
Xomnia Data Scientists are strong communicators and true team players who are able to lead projects from the ideation phase into implementation and deployment. They take on complex business problems from different domains such as fraud & anomaly detection, time series forecasts and recommender systems by working closely together with domain experts on the client side. From experience they know how to handle large volumes of data and apply the right kind of algorithm to the domain. Our Data Scientists take pride in the work they create and develop according to the best practices in coding, because models should live in production environments and not only in jupyter notebooks.