Key Skills

Job Description

We are a community open to everyone. One global team where everyone counts. Join the Canyon team and work at the cutting edge of the bike industry, with a job as versatile and exciting as the bikes we develop. All in an open, international atmosphere where teamwork, collaboration, true innovation, and a dynamic workplace are all part of our everyday. Ready to ride with us? THE ROLE Data is at the heart of how we grow, optimize, and innovate our e-commerce business at Canyon. As a Data Scientist in our Digital department, you build, operationalize, and scale data-driven models on Google Cloud Platform to drive customer lifetime value expansion, margin optimization, marketing mix modeling, and AI-native applications. Your data products will directly impact business operations and commercial decision-making across all global channels. YOUR JOB AS PART OF THE CANYON CREW Customer Intelligence: Designing and deploying Customer Lifetime Value (CLV) models that integrate customer, transaction, engagement data, and acquisition costs leverages complex enterprise data structures. Price Modeling: Building price elasticity algorithms using historical demand, inventory levels, and market signals optimizes gross margins across our bike portfolio. Acquisition Channel Optimization: Defining and deploying an advanced Marketing Mix Model (MMM) through Google’s Meridian framework measures and optimizes multi-channel advertising efficiency. Personalization Engine: Developing personalization systems for website and marketing touchpoints utilizes customer engagement and preference data. Predictive Marketing: Implementing propensity-to-buy and propensity-to-churn models fuels targeted email remarketing as well as predictive lookalike audiences across paid media channels. Technical Ownership: Building operational ML workflows in Google Cloud Platform (Gemini Agent Platform, BigQuery, Python) establishes robust pipelines for feature engineering, model tracking, and automated retraining. Data Preparation & Collaboration: Supporting data engineer:s hands-on with pipeline setup, data cleaning, and automation in BigQuery and dbt ensures ideal conditions for downstream model training. Evaluation & Quality Assurance: Monitoring ML infrastructure and model availability includes implementing version control and maintaining transparent documentation for all data products. Stakeholder Management: Partnering directly with commercial lead:s across CRM, Pricing, Sales, Performance Marketing, and E-Commerce translates business challenges into quantitative models with clear commercial targets. How You Become Part Of The Race Educational Background: A degree in data science, data analytics, statistics, applied mathematics, or a closely related quantitative field forms your academic foundation. Professional Experience: 4+ years of hands-on experience developing, deploying, and validating machine learning models in production environments within e-commerce, retail, or digital industries characterises your background. Technical Stack & Tools: Advanced Python proficiency (Scikit-learn, XGBoost, PyTorch/TensorFlow, Pandas), strong SQL skills for extracting data in BigQuery, and practical experience with API integrations and Git version control set your profile apart. Cloud & ML Ecosystem: Demonstrated expertise deploying models within Google Cloud Platform (Gemini Agent Platform, BigQuery ML, Meridian, Cloud Run) or equivalent environments (AWS/Azure) shapes your daily execution. Statistical Mastery: A solid foundation in supervised and unsupervised learning, time-series forecasting, statistical hypothesis testing, and price sensitivity/elasticity analysis defines your analytical approach. Commercial ML Expertise: Proven success delivering commercial ML use cases in e-commerce (CLV, acquisition cost optimization, pricing models, retention, personalization) drives business impact. Language Skills: Excellent English communication skills (both spoken and written) enable smooth and effective collaboration across international teams and business functions. HIGHLIGHTS ON YOUR CANYON TOUR The Canyon Crew & Culture: Combine energy and transparency in a global team. We promote a strong feedback culture, unique Canyon events, and inspiring crew rides. Your voice matters in creating an inclusive workplace where well-being is a priority. Feel Canyon (Product Perks): Unlock your passion for cycling! Enjoy exclusive discounts on bikes, gear, and apparel as part of our commitment to fueling your journey. Compensation & Rewards: Experience a rewarding career with a competitive market-based salary and generous paid time off. Your satisfaction is our priority. Life-Work Integration: Join us for a career that prioritizes balance through flexible and hybrid work options in a family-friendly environment. Impact & Development: Shape the future of mobility. We offer diverse career paths across operational, strategic, creative, or technical roles, where innovation and sustainability consistently challenge and inspire you.

Core Responsibilities

Develop, deploy, and scale production machine learning models and data products for customer lifetime value, pricing, marketing effectiveness, personalization, and customer retention. Build and maintain ML workflows on Google Cloud Platform, collaborate on data pipelines, monitor model quality, and partner with commercial teams to address business needs.

Requirements

A degree in data science, analytics, statistics, applied mathematics, or a related quantitative field is required, along with at least four years of hands-on experience deploying machine learning models in production. Candidates should have advanced Python and SQL skills, experience with cloud ML platforms and commercial e-commerce use cases, strong statistical knowledge, and excellent English communication skills.

Benefits

• Competitive Market-Based Salary
• Generous Paid Time Off
• Flexible Work Options
• Hybrid Work Options
• Bike, Gear, and Apparel Discounts
• Career Development Opportunities