Xomnia’s core team
We distinguish four different roles within our team to help you future-proof your organization:
Analytics translators
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.
They are fully focused on making an impact with data and AI at your organization. They make sure that relevant stakeholders are aligned and possible impediments are mitigated. They understand business challenges, think strategically, and excel in their result-driven, hands-on mentality. To know more, download our Way of Working whitepaper.
Data engineers
Xomnia’s data engineers are specialized 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. Trained to not overdesign, they follow and create the best practices in the field, ensure the right level of automation, and get the job done.
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. Their state-of-the-art knowledge and vast experience with proven technologies such as Spark, Scala, Cassandra, Airflow, Kafka and Kubernetes enables them to use the right stack for the right problem.
With their technical and social skills, our data engineers easily connect with your internal team, and remain focused on achieving your goals together! For examples of our previous projects, click here.
Data scientists
Xomnia's data scientists are strong communicators and true team players who can lead and execute projects from ideation into implementation and deployment. They take pride in the work that they create, and develop according to the best practices in coding, because models should live in production environments - and not only in Jupyter notebooks.
Our data scientists tackle complex cases where data and AI are an enabler to value creation. They develop solutions within areas such as recommendation systems, price and promotion forecasting, IoT and sensor data analytics, and natural language processing. Based on their experience, they know how to handle large amounts of data and how to apply the right kind of algorithm in the optimal way for the specific use case. They often work closely with domain and technical experts on the customers' side, and usually develop on one of the major cloud platforms. For examples of our previous projects, click here.
Machine learning engineers
Xomnia's machine learning engineers are broadly experienced in both building and productionizing AI models. They can go all the way from conceiving new models to solve business problems, to deploying them using state-of-the-art techniques to create true impact. This ranges from building data pipelines, to data exploration and modelling, to productionizing models and finally deploying them in a cloud environment.
In doing so, they follow and set the best practices in modelling, programming, automation and CI/CD. In many cases, this best-of-both-worlds profile allows you to rapidly go from idea to meaningful impact.
