Application Guide
How to Apply for Staff Data Scientist (AI Transformation)
at Fastned
🏢 About Fastned
Fastned is unique as a European fast-charging network company that exclusively uses renewable energy, directly contributing to the acceleration of sustainable mobility. Working here means being at the intersection of cutting-edge technology and meaningful environmental impact, with a mission-driven culture focused on decarbonizing transportation.
About This Role
This Staff Data Scientist role involves leading AI transformation across Fastned by coordinating cross-functional AI workstreams and owning data science initiatives from discovery to implementation. You'll drive strategic impact by developing models (simulations, ML, GenAI, causal inference) that optimize charging network operations and customer experience while coaching team members and managing stakeholder change.
💡 A Day in the Life
A typical day might involve coordinating with the AI Leadership Task Force on transformation priorities, coaching data scientists on simulation model development, and working with operations teams to implement AI-driven optimizations for charging network performance. You'd balance strategic planning for AI adoption with hands-on model review and stakeholder alignment sessions.
🚀 Application Tools
🎯 Who Fastned Is Looking For
- Has 7+ years experience with proven ability to deploy ML models to production in Python, specifically in energy, mobility, or infrastructure domains
- Demonstrates strong leadership through influence with experience coordinating cross-functional initiatives and managing executive stakeholders
- Possesses deep expertise in simulation-based methods and causal inference for optimizing complex systems (not just predictive modeling)
- Shows experience driving organizational AI transformation and change management, not just technical implementation
📝 Tips for Applying to Fastned
Highlight specific experience with simulation modeling or causal inference in infrastructure/energy contexts, not just ML prediction tasks
Demonstrate how you've led AI transformation initiatives in previous roles, including change management and stakeholder coordination
Show Python production deployment experience with concrete examples of models you've taken from development to live implementation
Research Fastned's charging network and suggest one specific AI opportunity (e.g., demand forecasting, pricing optimization, grid balancing)
Emphasize sustainability alignment - connect your data science experience to environmental impact and renewable energy goals
✉️ What to Emphasize in Your Cover Letter
['Your experience leading AI/DS initiatives end-to-end with specific examples of organizational change management', 'How your simulation or causal inference work has optimized complex systems (ideally in energy, mobility, or infrastructure)', "Alignment with Fastned's mission of accelerating sustainable mobility through renewable energy", "Specific ideas for how AI could transform Fastned's charging network operations or customer experience"]
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Fastned's charging network coverage, pricing models, and partnership ecosystem across Europe
- → European renewable energy grid challenges and how EV charging interacts with energy markets
- → Fastned's sustainability reports and specific decarbonization targets
- → Competitors in European fast-charging space and their technology approaches
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Focusing only on predictive ML without demonstrating simulation or causal inference expertise
- Presenting as purely technical without showing leadership through influence and change management experience
- Applying with generic AI experience not connected to infrastructure, energy, or mobility domains
📅 Application Timeline
This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.
Typical hiring timeline:
Application Review
1-2 weeks
Initial Screening
Phone call or written assessment
Interviews
1-2 rounds, usually virtual
Offer
Congratulations!