Senior Data Scientist Assortment Quality

About bol

Bol is the largest online retailer in the Netherlands and Belgium.

Position

How do you make our customers happy?

Bol.com wants to maintain customers’ and partners’ complete trust in our platform. So keeping our current customers and partners happy, and winning over new ones, means our job description includes assessing, elevating, and safeguarding the quality of each and every one of our 31 million products. In fact, the Assortment Quality team has made this a top corporate priority, and we are committed to vetting our entire assortment (yes, we mean 100%) by the end of 2025. Do you have the data science chops to help us reach that ambition?

The biggest challenge

Considering the vast size of our catalog, manually verifying that every item meets our standards is simply not an option; we need (preferably infinitely) scalable solutions to help us achieve our ‘reliability dream.’ This entails flagging ‘forbidden’ and unwanted products before they even reach our retail tech platform. For example, unsafe toys (e.g., choking hazards), counterfeit articles, products that are detrimental to animal welfare, unironically hilariously/ dangerously misinfomative self-help books, and – obviously – anything that would be illegal to sell. And that’s only scratching the surface because we also want to develop and implement policies for products that are very much welcome but might pose risks, such as cosmetics and food products that contain allergens. Moreover, we are eager to add additional objective insights to our product pages (e.g., sustainability scores) to help our customers differentiate options. In short: we have lots to do, and lots of advanced algorithms to develop, train and implement.

What you’ll do as a Senior Data Scientist Assortment Quality?

In this highly impactful role, you’ll join the team of data scientists and machine learning engineers that is propelling our assortment quality to the stratosphere. We do so by conceptualizing and building scalable solutions that enhance the quality of our assortment and all product listings. Analyze large product quality and customer feedback data sets, and develop models that help us understand what drives product quality and customer satisfaction. We firmly believe in the value of iterative experimentation, so exploring different ideas and approaches to determine what is technically feasible AND nets the desired outcomes is an integral part of the job. As is building and fine-tuning predictive models that help identify potential issues before they develop into customer problems. Additionally, delight operational departments with scalable methods to adopt more effective ways of working. Of note: while this is a ‘hardcore’ data science position, you also need to discuss topics with a wide range of stakeholders. You will regularly team up with product managers, engineers, and DS peers to ensure we are optimally leveraging the data to improve the quality of our platform.

We would love to meet over coffee if you are open to feedback, eager to share opinions, and subscribe to our agile and iterative approach. The ability to juggle immediate results and long-term viability is often key to success, especially if you combine that quality with a getting sh*t done mindset and feel comfortable in a setting where the end result is still very much a work in progress.

Your qualification

3 reasons why this is (not) for you

• No, because you don’t mingle. Business colleagues are oil to your water. Or vice versa. Either way, you don’t mix
• No, because you speak in mathematical tongues. You’d love to explain the added value of your models but can’t express your thoughts in English
• No, because you ideate only. You’re great at coming up with ideas, but actually fleshing those out and bringing them into production? That’s not part of the job, is it?
• Yes, because you live data science. As evidenced by your seniority (4+ years of relevant experience) and skills in Machine Learning / Deep Learning, NLP / Information Retrieval techniques, Python, SKLearn, TensorFlow and/or PyTorch, as well as a proven ability to write complex SQL queries (e.g. BigQuery)
• Yes, because you breathe data. In the form of happy little word clouds. That is to say, you love to spread the data science gospel and have a knack for explaining data science principles to non-data scientists
• Yes, because you make data science work. Advancing the field of data science would be a nice bonus, but you got into this line of work to solve real-life problems

Additional details

Where you will work

As a Data Scientist, you’ll be at the center of our data-intensive landscape. Our business model is tech-focused, and achieving data-driven improvements and innovations for our customers is our bread and butter. The bol.com data science community is a growing team of data-savvy professionals that consists of Data Scientists, Machine Learning Engineers, Data Engineers, and Software Engineers. And because we work in cross-functional teams, with ample representation from the business, you can always see the big picture. Professional success in data science requires more than any university can teach you, and bol.com is the perfect place to complete your education. The setting? Informal, pragmatic, and innovative. Our success is based on collaborating as equals and continuously learning from each other. You can achieve great things alone. And even better things together.

Your application process

• Your application - Carefully, we take a look at your application. You will hear from us soon to let you know if we invite you for an interview
• First contact - We’ll contact you to walk you through the process and take the first step to set up an interview. And since we’re already talking: feel free to ask any questions you may have
• First date - During the first interview we’ll get to know each other. We want to find out more about you, your work experience and skills
• Your next interview - Before this interview will take please we will ask you to take an online HR assessment and a technical assessment. We’ll also discuss the position and the team in depth 
• Is this love? - Two 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