Senior Data Scientist

About Peter Park

Peter Park facilitates barrier-free digital parking solutions across Germany, Austria, Switzerland, and Italy, serving over 450 B2B clients and managing more than 90,000 parking spaces using advanced computer vision in place of traditional gates. Their system handles millions of transactions underpinned by a comprehensive data model. The company aims to revolutionize urban parking management by replacing barriers and tickets with seamless mobile payment options, enhancing the daily driving experience while optimizing urban space usage for a sustainable environment.

Role Summary

As a Senior Data Scientist, you will transform vast datasets into actionable insights and business decisions that generate revenue. Collaborating closely with technical leaders, you will identify crucial data patterns, develop scalable analytical tools, and influence product development through evidence-based findings. Ownership, impact-driven work, and engagement with real-world data are key to succeeding in this role.

Key Responsibilities

• Analyze extensive datasets to detect trends, patterns, and irregularities within the parking and payment systems.
• Formulate and test data-driven hypotheses to boost revenue and detect early risks and opportunities, directly impacting significant revenue streams.
• Maintain and optimize strategies focused on revenue enhancement continuously.
• Develop statistical and analytical tools to extend the product's capabilities, aiding B2B clients in smarter parking management.
• Provide insights on user behavior, product interaction, and customer satisfaction to guide product decisions.
• Collaborate with data engineers to ensure data accessibility, quality, and accurate modeling.
• Create reporting solutions and dashboards to empower business teams with self-service data insights.
• Base models and analyses on thoroughly validated and reliable data.
• Build and maintain data pipelines for collection, processing, and transformation needs.
• Stay informed on advancements in data science, machine learning, and applied AI, contributing to team growth through mentorship and sharing best practices.

Expertise and Qualifications

• Significant practical experience in data science, machine learning, and analytics demonstrated by measurable impact, ownership, and continuous improvement rather than just tenure.
• A degree in quantitative disciplines such as computer science, statistics, mathematics, physics, or engineering.
• Strong curiosity and analytical skills with a problem-solving mindset to understand data and underlying processes.
• Proven ability in data analysis, statistical modeling, and applying machine learning techniques.
• Advanced proficiency in Python programming, SQL querying, data visualization, and version control using Git.
• Experience with cloud platforms and data infrastructure including AWS, Aurora PostgreSQL, Redshift, and BI tools like Tableau.
• Expertise with data manipulation libraries (Pandas, NumPy) and machine learning frameworks (Scikit-Learn, PyTorch).
• Collaborative and cross-disciplinary teamwork approach.
• Fluency in English at the C1 level both written and spoken.

Work Environment

• Standard working week of 40 hours based on mutual trust.
• Hybrid working model with three days in the Munich office and two days remote within the EU.
• Permanent employment contract.

Employee Benefits and Perks

• Company pension scheme and corporate perks.
• JobRad bike leasing option and choice between a subsidized public transport ticket or EGYM Wellpass membership.
• Flexible working hours and remote work option within the EU.
• Modern workspace with height-adjustable desks, top-tier Apple hardware including MacBook M4 Pro with 48GB RAM and a large 37-inch curved monitor.
• Access to advanced AI models, dedicated MCP servers, and agentic tooling to excel in role.
• Provision of healthy snacks like fruits, nuts, and muesli, subsidized office catering, and weekly team lunches.
• Stable financial environment coupled with a vibrant startup culture emphasizing growth and well-being.

Recruitment Process

• Initial response within 48 hours.
• An HR interview to discuss experience and expectations.
• A live assessment presenting challenging scenarios.
• A technical challenge to demonstrate relevant skills.
• An in-depth discussion with the Head of Product on role expectations.
• On-site meeting at the Munich office to experience company culture and meet team members.