How do you make our customers happy?
By designing algorithms that make the customer journey perceptibly better. Because that’s what our Data Science & Advanced Analytics team does every day; leverage data to enhance the customer experience. For example, by utilizing machine learning to predict sales patterns, personalize the shopping experience, detect fraud and add relevant information to millions of products. Can you unlock more of the vast potential of data science for our customers?
Your responsibilities as Data Scientist Forecasting
As Data Scientist, you use the vast amounts of data at our disposal to create forecasts which drive smart decision making. A high degree of accuracy is only part of the equation; ideally, every forecast should make the lives of customers and partners a little easier. Therefore, we make sure we understand the use case first and build a simple model to validate this understanding. Once we are certain we are actually solving the right issue, and provide the right level of detail, we improve forecasts step by step, until we eventually hit the bullseye.
As a centralized forecasting team, we support various departments with relevant forecasts by leveraging our knowledge and technology over a broad range of use cases. As an example, we utilize various time series and ML techniques to create forecasts and we get to pick (or even combine) the best of both worlds to get the optimal results. This also allows us to feed the result of one forecast into the next to make the impact of a single improvement trickle down to all forecasts made. Finally, the scale at which we forecast – for instance on an individual product level for half a year ahead – provides unique challenges and makes the work addictively fun.
Because we help others make better decisions, the job comes with lots of user interaction. We listen to what users want to achieve. And what is holding them back. In close collaboration, we turn their challenge into a model which we improve on together. This means strong communication skills are a necessity, since it’s up to you to explain how a forecast was created and to gain the trust and commitment of colleagues. After all, they will base their decisions on the numbers you provide.
To achieve our goals, we use a mix of Python and Java to strike the right balance between flexibility and robustness. Our Google cloud infrastructure allows us to use BigQuery and Storage for data wrangling and Airflow for proper orchestration of the jobs we run. You’ll also be the ambassador for your domain by presenting the complex theory to bol.com colleagues from a practical perspective, while highlighting the customer value created.
3 reasons why this is(n’t) for you
- Because you want to apply your PhD or Master’s degree in Econometrics, Applied Sciences, Artificial Intelligence or Data Science to make the lives of over 10 million customers easier and more fun (3+ years working experience is a strong preference)
- Because you’re at home wrangling large datasets and creating new features to constantly run experiments and tweak your models to get the best performance possible
- Because you understand that to solve a problem, you need to understand it first and this is best done by talking to domain experts
- Because you’d rather have a cool model than a happy user of your forecasts
- Because you have no affinity with software engineering and store your scripts as _v3_new_experiment_feb20.ipynb rather than create a new branch
- Because discussing ideas with direct colleagues would be a waste of time; don’t you already know everything?
Where you’ll work
As Data Scientist you’ll be at the center of our data-intensive landscape. Our business model is focused on technology, and data-driven improvements that drive innovation for our customers are our bread and butter. The Data Science & Advanced Analytics is a growing team of data savy professionals, consisting of over 50 data Scientist, Machine Learning Engineers, Data Engineers and Software Engineers. The cross-functional teams, with ample representation from the business units, can also give you a complete picture of the organization. Professional success in data science requires more than any university can teach you, and bol.com is the perfect place to learn the rest. The setting is informal, pragmatic and innovative. Our success is based on collaborating as equals and continuously learning from each other. You can achieve great things alone. Even better things together.
What you get
How it works
Your applicationCarefully, we take a look at your application. Within 2 weeks you know if we invite you for an interview.
First contactWe call you to set up an interview. And since we’re already talking: feel free to ask any question you may have.
First dateIn this first interview we’ll get to know each other. We want to find out more about you. Work experience is interesting, but we also want to find out more about you as a person. Together, we’ll find out if this job is a match made in heaven.
Your next interviewBefore the next interview we will ask you to take an online assessment. We’ll also discuss the position and your team in depth.
Is this love?2 interviews are usually enough to see if it’s a match. And if you agree… well, it’s the beautiful beginning of your career at bol.com :)