Peter Park runs barrier-free digital parking across Germany, Austria, Switzerland, and Italy — serving 450+ B2B customers and 90,000+ parking spaces with computer vision instead of gates. Behind it sits a rich data model and millions of transactions.
We're looking for a Senior Data Scientist to turn that data into decisions and revenue. You'll work closely with our technical leadership to find the patterns that matter, build tools that scale, and shape our product with evidence. If you value ownership, real-world data, and seeing your work move the business, you'll fit right in.
Activities
- Analyze large datasets to surface trends, patterns, and anomalies across our parking and payment ecosystem.
- Develop data-driven hypotheses that drive revenue growth and flag risks and opportunities early directly impacting millions in revenue.
- Continuously monitor and refine revenue-enhancing strategies.
- Extend our product with statistical and analytical tooling that helps B2B customers manage their parking areas smarter.
- Deliver insights on user behavior, product usage, and customer satisfaction to steer product decisions.
- Partner with our data engineers to ensure the data you need is modeled, accessible, and trustworthy.
- Build reporting and dashboards that let business teams self-serve on insights.
- Ground your models and analyses in validated data you can stand behind.
- Build data pipelines for collection, processing, and transformation.
- Stay ahead of developments in data science, ML, and applied AI, and help lift the team through best practices and mentorship.
Requirements
- Real seniority in data science, ML, and analytics with real-world data measured by impact, ownership, and drive for improvement, not just years on paper.
- A degree in a quantitative field (computer science, statistics, mathematics, physics, engineering, or similar).
- A deep curiosity about data and the processes behind it, with strong problem-solving and analytical instincts.
- Proven experience in data analysis, statistical modeling, and machine learning.
- Expert-level Python, SQL, data visualization, and Git.
- Experience with cloud computing, data warehouses, and NoSQL databases (we run AWS, Aurora PostgreSQL, and Redshift, with Tableau as our BI layer).
- Strong command of data manipulation libraries (Pandas, NumPy) and ML frameworks (Scikit-Learn, PyTorch).
- A collaborative, cross-functional working style.
- Excellent written and spoken English (C1).
Application Process
- Initial Contact: We’ll get back to you within 48 hours.
- HR Interview: Discuss your experience and expectations with our HR team.
- Live Assessment: Complete a technical exercise designed to challenge you with scenarios beyond your usual experience.
- Tech Challenge: Tackle a problem in a familiar context to demonstrate your technical skills and approach.
- Leadership Conversation: Dive deeper into the role and expectations with the Head of Product.
- On-Site Meeting: Visit our Munich office, meet more of the team, and experience our culture firsthand.