DATA SCIENCE

Overview

We employ over half a million people around the globe across postal services, international express delivery, forwarding and contract logistics. Not surprisingly, our activities generate a lot of data. We believe that our data is the key to unlocking untapped potential in our company – and we are looking for ambitious data scientists and data engineers that can help us enable our digital transformation journey.

Machine learning, mathematical optimization and data engineering are our domains. If you would like to know more about us, check out the information below – and don’t hesitate to give us a call. We are always happy to answer any questions you may have.

What we do

PREDICTIVE ANALYTICS

We love employing machine learning to give our business a glimpse of the future. What is the warehouse demand next month? At what time will shipments be delivered? Is a particular customer likely to change to a competitor? The questions we get from our business are challenging – and their requirements are ever-changing. The variation in the problems that we solve for our business is also one of the key reasons why our data scientists must be comfortable with time-series forecasting, classification and statistical analysis.

PRESCRIPTIVE ANALYTICS

Prescriptive analytics is the natural successor to predictive analytics. When we perform predictive analytics, it is (not surprisingly) to tell something about the future. After we have generated insights from our predictive models, we typically venture into prescriptive analytics to help our business partners make the most of this information.

ROUTING OPTIMIZATION

As the biggest logistics company in the world, we can also boast one of the most extensive transportation network in the world. However, size comes at the expense of complexity and our data scientists play a significant role in ensuring that shipments are transported both timely and efficiently. Delivering logistics services requires much more information than just point A for pick-up and point B for delivery. What is the most efficient route? Do we optimize on time or cost? What mode of transport should we use? From where should we fly? How do we consolidate? These are just a fraction of the questions we are expected to solve.

How we work

Diversity

As a group committed to diversity, data scientists and engineers from all backgrounds and different skill sets bring their expertise to our data science teams. Our data science community consist of physicists, statisticians, natural scientists, computer scientists and engineers from various fields. Each individual brings his or her own expertise to company, to come up with the best solutions.

Data science community

DHL Group employs many data scientists among divisions and global locations and we prioritize collaboration across all our divisions and location. We arrange community gatherings such as our regional Lunch and Learn meetings, where our scientists share project experiences, and our annual Data Science Day, where our data scientists get together in Bonn for a full day of internal and external presentations and information exchange. For more academic endeavors, some data scientists have frequent meetings in our Data Science Journal Club, where the topic is cutting-edge data science research.

External collaborations

In addition to our internal community, we also have ties with external data science communities. We do occasional exchanges with the data science departments of other companies on methods and use cases. We also share our knowledge in public events like regional Meetups.

Do you have an innovative idea for your data science thesis that relates to data analytics and the logistics industry? Then we look forward to hearing about it. We do occasionally have students working on their theses on-premise.

Continuous learning

In this challenging world of competition, our data scientists are in full control of their own development – with the sparring and mentorship of our data science colleagues. We bring our new joiners up to speed in our data science bootcamp – covering data science from a business and technical perspective. To keep up with the latest advancements in both literature and technology, our teams participate in workshops and seminars all around the world. Furthermore, we conduct regular internal trainings and participate in external trainings where we see a need for improvement. It is absolutely vital for us that our data scientists and engineers continue to learn – for the sake of themselves and our company.

Corporate data lake

Data is an asset – and, in DHL Group, we consider data to be as important an asset as our hubs, planes and trucks. It is imperative for us that all data scientists in the Group have access to data from a reliable and easy to reach source. Our corporate big data infrastructure, more colloquially known as our Data Lake, is currently under implementation – so if you are a data engineer looking for an exceptional opportunity, this is it. We aim to enable our data scientists to deploy their big data and machine learning solutions, with a single click, without worrying about scalability.

slide 1 of 2 Diversity As a group committed to diversity, data scientists and engineers from all backgrounds and different skill sets bring their expertise to our data science teams. Our data science community consist of physicists, statisticians, natural scientists, computer scientists and engineers from various fields. Each individual brings his or her own expertise to company, to come up with the best solutions. Data science community DHL Group employs many data scientists among divisions and global locations and we prioritize collaboration across all our divisions and location. We arrange community gatherings such as our regional Lunch and Learn meetings, where our scientists share project experiences, and our annual Data Science Day, where our data scientists get together in Bonn for a full day of internal and external presentations and information exchange. For more academic endeavors, some data scientists have frequent meetings in our Data Science Journal Club, where the topic is cutting-edge data science research. External collaborations In addition to our internal community, we also have ties with external data science communities. We do occasional exchanges with the data science departments of other companies on methods and use cases. We also share our knowledge in public events like regional Meetups. Do you have an innovative idea for your data science thesis that relates to data analytics and the logistics industry? Then we look forward to hearing about it. We do occasionally have students working on their theses on-premise.Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book.

Exemplary projects

Forecasting with machine learning

As the national postal service for Germany, last year, more than 118000 couriers delivered over 5.9 million parcels and 49 million letters per working day. Accurately forecasting these volumes is challenging but also crucial to efficiently run our business.
Until a few years ago, the letter and parcel volume forecasts were mainly based on the experience of business experts. Today we use machine learning to improve them and to provide forecasts on different granularities and time horizons.

Key players

SEVERIN
Data Scientist
PhD Engineering

“I enjoy working at the Data Analytics Center of Excellence because of the vast range of interesting topics, the opportunity to specialize in focus areas of my interest and the chance to bring benefits to our customers and the company.”

MINH
Data Scientist

“Forecasting presents many exciting challenges to a Data Scientist. I consider myself lucky to be able to tackle these problems among like-minded colleagues who are all constantly striving to solve problems better for our business partners. In the meantime, we also aim to develop ourselves and keep abreast of the fast moving, ever expanding and thrilling world of Machine Learning.”

PRAKRITI
Data Scientist

“Working at DHL Group has provided me with an excellent opportunity to develop data science solutions using latest technologies which directly impact and potentially improve the business processes. Without doubt, what makes it an amazing place to work is the team diversity, positive spirit and open culture among colleagues which encourages development for all.”

slide 3 of 3 GABRIELA Data Scientist MSc Data Mining and Knowledge Management “Working at DHL Group has provided me with an excellent opportunity to develop data science solutions using latest technologies which directly impact and potentially improve the business processes. Without doubt, what makes it an amazing place to work is the team diversity, positive spirit and open culture among colleagues which encourages development for all.”

PERSCRIPTIVE STAFF SCHEDULING

In the earlier predictive analytics example, we first helped the business to forecast volumes using machine learning. With this information, we worked closely with the business to create a prescriptive staff scheduling algorithm to optimize the working schedules for our colleagues in the distribution centers. Thus, the volume forecast helped to meet several objectives for our business.

Key players

HENNING
Data Science – Team Lead

"Delivering millions of letters, parcels, and shipments of all sizes to customers every day requires an enormous amount of decisions to be taken every day and generates a huge amount of data. Using this data to inform and improve the decisions is a huge opportunity both for the company as well as for myself.

FELIX

Data Scientist
PhD Physics

"As a Data Scientist at DHL Group I enjoy working on a vast range of exciting topics from various business areas with an immediate and tangible impact, while constantly learning and developing. On top, doing so within a team of curious and great personalities is especially rewarding."

slide 1 of 2 STEFAN Data Science – Team Lead Diploma Business Mathematics with major in mathematical optimization "The projects and data science problems we face are both challenging and diverse; as a consequence, I learn something new every day while we generate a measurable impact for the business. The impact of our projects truly enables us to play an important role in the digital transformation of our company. All this happens while having fun at work with colleagues from different cultural and professional backgrounds."

OPTIMISING DELIVERIES

Think back to our previous examples in predictive and prescriptive analytics. We have forecasted the incoming volume of letters and parcels; we have optimized the staff working on-site, now it’s time to deliver. While our previous exercises generated significant value to the business – the delivery of letters and parcels is of utmost importance to any logistics company.

The natural next step was therefore for our operations research colleagues to optimize the routing of our delivery personnel to ensure that the whole process is as efficient as possible. The Traveling salesperson problem is omnipresent in logistics and we are always looking for talented operations researchers to optimize our routing

Key players

ANDRÈ

Data Scientist – Operations Research
PhD Mathematical Optimization

"We are confronted with a variety of difficult problems for which no standard solution exists. To effectively tackle these problems we have to combine different methods, which we may already be familiar with – or that we have to learn by doing research. I really enjoy this challenging work, which requires a lot of creativity."

THOMAS

Data Scientist – Operations Research
PhD Computer Science

"Working at DHL Group allows me to solve real problems and to immediately observe the effect of my solutions. I learn something new every day and, what I find especially cool, is the combination of data science and optimization."

slide 2 of 2 THOMAS Data Scientist – Operations Research PhD Computer Science "Working at DHL Group allows me to solve real problems and to immediately observe the effect of my solutions. I learn something new every day and, what I find especially cool, is the combination of data science and optimization."

THE TOOLS WE USE

At DHL Group, we evaluate each of our projects individually and select the best set of tools that can help us solve the business problems we are facing.

MACHINE LEARNING

PROGRAMMING LANGUAGES

OPERATIONAL RESEARCH

BUSINESS INTELLIGENCE

BIG DATA

APPLICATION PROCESS

Get in touch

KATRIN

VP DATA ANALYTICS

Get in touch with me about our projects.

LinkedIn: Katrin König

Email: katrin.koenig@dpdhl.com

(+49) 228 1896 3374

Find out more about what we are saying about Data Science on Linkedin

#dpdhldatascience

Overview

​​​​​​​What we do

PREDICTIVE ANALYTICS

PRESCRIPTIVE ANALYTICS

ROUTING OPTIMIZATION

How we work

Diversity

Data science community

External collaborations

Continuous learning

Corporate data lake

Exemplary projects

Forecasting with machine learning

Key players

PERSCRIPTIVE STAFF SCHEDULING

Key players

FELIX

OPTIMISING DELIVERIES

Key players

ANDRÈ

THOMAS

THE TOOLS WE USE

THE TOOLS WE USE

MACHINE LEARNING

PROGRAMMING LANGUAGES

OPERATIONAL RESEARCH

BUSINESS INTELLIGENCE

BIG DATA

APPLICATION PROCESS​​​​​​​

Get in touch

KATRIN

What we do

APPLICATION PROCESS