About DHL IT Services and the AI & Analytics team
At DHL IT Services, we are designing, building and running IT solutions for the whole DPDHL globally.
The AI & Analytics team builds and runs solutions to get much more value out of our data. We help our business colleagues all over the world with machine learning algorithms, predictive models and visualizations. We manage more than 46 AI & Big Data Applications, 3.000 active users, 87 countries and up to 100,000,000 daily transaction.
Integration of AI & Big Data into business processes to compete in a data driven world needs state of the art technology. Our infrastructure, hosted on-prem and in the cloud (Azure and GCP), includes MapR, Airflow, Spark, Kafka, jupyter, Kubeflow, Jenkins, GitHub, Tableau, Power BI, Synapse (Analytics), Databricks and further interesting tools.
We like to do everything in an Agile/DevOps way. No more throwing the “problem code” to support, no silos. Our teams are completely product oriented, having end to end responsibility for the success of our product.
Who do we look for?
Currently, we are looking for MLOps/Data Science Engineer. In this role, you will have the opportunity to design and develop solutions, contribute to roadmaps of Big Data architectures and provide mentorship and feedback to more junior team members. We are looking for someone to help us manage the petabytes of data we have and turn them into value.
Does that sound a bit like you? Let’s talk! Even if you don’t tick all the boxes below, we’d love to hear from you; our new department is rapidly growing and we’re looking for many people with the can-do mindset to join us on our digitalization journey. Thank you for considering DHL as the next step in your career – we do believe we can make a difference together!
What will you need?
- University Degree in Computer Science, Information Systems, or related field
- 2+ years of experience in the Data Science Engineer role
- Strong analytic skills related to working with structured, semi structured and unstructured datasets
- Statistics / Mathematics: Data Quality Analysis, Data identification, Hypothesis testing, Univariate / Multivariate Analysis, Cluster Analysis, Classification/PCA, Factor Analysis, Linear Modeling, Time Series, distribution / probability theory.
- Python, R
- Awareness of Apache Spark, Hadoop
- Awareness of Agile / Scrum ways of working
- Identify the right modeling approach(es) for given scenario and articulate why the approach fits
- Assess data availability and modeling feasibility
- Review interpretation of models results
- Experience in Logistic industry domain would be added advantage
You should have:
- Github
- Kubernetes
- Kubeflow
- Docker
- Python (Preferably ML knowledge)
- Github Actions / Jenkins
- Kibana / Grafrana
- Linux/Bash
Language requirements:
- English – Fluent spoken and written (C1 level)
An array of benefits for you:
- Annual Leave – 42 days off apart from Public / National Holidays
- Medical Insurance - Self + Spouse + 2 children. An option to opt for Voluntary Parental Insurance (Parents / Parent -in-laws) at a nominal premium covering preexisting diseases
- In House training programs - professional and technical training certifications
- Flexible Work options
