Key Skills

Job Description

How do you make our customers happy? From personalized recommendations to demand forecasts, and from fraud signals to ‘automagic’ price adjustments: the decisions shaping the experience of 14 million customers are increasingly inspired, or even made, by models. As Head of Data Science & AI, you make sure those models (and the people who build them) deserve that trust. Your first six months are all about elevating our data craft and strengthening the data science community, including its leadership. How can we build a data science community that is ahead – and stays ahead – of the curve? How do we attract and retain great minds? It’s up to you to build a world-class data science community where people and AI thrive and work together. The biggest challenge Right now, data science is distributed, with pockets of brilliance that don't always add up to a shared standard. You make sure that it does. How do you set a quality bar high enough to matter and practical enough that data scientists want to clear it? You need to bring bol's data scientists, spread across every domain, into one coherent way of working. You must also set the strategy for where bol invests in Data Science and AI capabilities, helping determine where domain-specific innovation adds value, and where shared AI capabilities (or AI-adjacent data products) create leverage. The second challenge has to do with capital and control. What is the right balance between letting domains move fast and keeping AI coherent, trustworthy, and safe? You decide where central investment goes. And which models are critical enough, because of risk, scale, or consequence, to own outright and where autonomy is the better call. What you'll do as the Head of Data Science & AI You'll define and own bol's data science and AI vision and strategy, reporting to the Director of Data, Analytics & AI. Initially, you primarily zoom in on craft coherence and excellence. You have a dotted-line relationship with data scientists embedded across bol's domains, and a small core team to help you build shared standards, tooling, and training programs for the data science community. Success is measured by outcomes. Within the data science community, and beyond, because the more impact we create for customers, partners and business stakeholders, the better. In short: - Define and own the data science and AI strategy, aligned with product, technology, and business priorities — including where we invest, and clear build / buy / reuse choices - Develop, evangelize and elevate our data science craft: standards, tooling, training, and quality bar for our data scientists, company-wide, most of whom report elsewhereGrow and lead a central data science and AI team, scaling as scope expands - Oversee the full model lifecycle: development, validation, deployment, monitoring, and retraining - Enable domain teams to build and deploy AI with confidence, through shared patterns, standards, and expert support - Partner closely with Data Platform & Engineering to develop and operate models at scale - Ensure AI at bol meets legal, ethical, and regulatory obligations, embedding transparency, human oversight, and responsible-AI principles into the design and use of models - Lead and develop the central data science and AI teams, set the quality bar and build the talent, career paths, and learning practices that keep bol's data scientists at the forefront Why you can make a difference You know how to create momentum, drive execution, and make clear decisions in environments where trade-offs and ambiguity are unavoidable. You have deep expertise in data science and machine learning, having applied AI in complex, real-world environments. You understand how AI integrates with products, engineering platforms, and analytics, and design with practicality in mind. You've successfully scaled data science teams and capabilities before, and can translate advanced analytical concepts into outcomes a business audience can grasp. You can expertly weigh innovation against risk, scale against rigor, and speed against explainability. Lastly, you set scientific quality standards that are high enough to impress and practical enough to apply. Where you'll be working You'll join bol's Data, Analytics & AI organization and report to the Director of DA&AI. Here, you’ll lead the central data science and AI function with a direct line to your core team, and a dotted line to the scientists embedded across the domains that deploy models. Your peers run the data, analytics, and platform functions you depend on and enable: where the Head of Data Products & Governance makes the data trustworthy, and the Head of Product Analytics turns data into decisions, you ensure the models built on top of our data are sound, scalable, and trustworthy. AI has become an integrated component of our infrastructure, and needs an owner who can make it a key component. You won't be running a lab. You'll ensure that when bol bets on a model, the odds are overwhelmingly in our favor. Something for you? Craft builder: You excel at harmonizing and uplifting a craft, and know how to drive heartfelt adoption across domains, without formal authority. Responsible by conviction: Explainability, oversight, and responsible AI are what separates a model worth deploying from a black box with shiny metrics. Central-and-distributed thinker: You can hold the hybrid in your head. You own what's critical, enable the rest, and tell the difference under pressure without defaulting to demanding absolute control or inviting chaos. Nothing for you? Notebook romantic: Your joy is the modeling process. Lifecycle management, safeguarding governance, and overseeing multiple models in production sound like administrative chores. Explosive sprinter: "Responsible AI" is never a bottleneck for innovation. You'll always ship the best-performing model and address explainability if a regulator asks (hint: it’s their job to ask). Pure centralizer: You'd rather own every model yourself than trust a domain team with a standard. We take pride in our B Corp certification and strive for continuous improvement every day. Our annual bonus is tied to sustainability goals, and we are committed to equality and equal opportunities for all.Perks of having a blue heart 29 days: to recharge Travel costs: Public transport, car, parking & charging covered Pension plan: 75% premium covered Annual bonus: Based on sustainability goals

Core Responsibilities

Define and lead the company-wide data science and AI strategy, establish shared standards and practices, and build a central team that supports data scientists across business domains. Oversee the model lifecycle and responsible AI practices, while enabling teams to deliver scalable, trustworthy models that create business and customer impact.

Requirements

The role calls for deep data science and machine learning expertise, experience applying AI in complex real-world settings, and a track record of scaling data science teams and capabilities. The successful candidate can set practical scientific quality standards, lead through ambiguity and influence across domains, and balance innovation, business outcomes, explainability, and risk.

Benefits

• 29 Days Of Leave
• Travel Costs Covered
• Pension Plan With 75% Of The Premium Covered
• Annual Bonus Based On Sustainability Goals