Data Scientist Early Hire, Full Model Ownership, B2C SaaS in Germany at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Scientist Early Hire, Full Model Ownership, B2C SaaS based in Germany.

This is a unique opportunity to join a growing data team at an early stage and play a foundational role in shaping how machine learning and experimentation drive business outcomes. You will take full ownership of predictive models from problem definition through deployment, monitoring, and performance evaluation. Working closely with Product, Growth, Engineering, and Finance teams, you will help transform data into actionable insights that influence product strategy and revenue growth. The role offers significant autonomy, broad business exposure, and the chance to build scalable data science practices from the ground up. You'll work in a fast-paced, remote-first environment where experimentation, innovation, and measurable impact are highly valued. If you enjoy solving complex business problems with data and seeing your work directly influence company performance, this role offers exceptional ownership and visibility.

• Design, build, validate, deploy, and monitor machine learning models that support key business objectives such as churn prediction, customer lifetime value forecasting, propensity modeling, uplift modeling, and recommendation systems.
• Own the complete machine learning lifecycle, including feature engineering, model development, evaluation, deployment, monitoring, and continuous optimization.
• Monitor production models, ensuring performance remains accurate and relevant as user behavior and product dynamics evolve.
• Design and analyze experiments, including A/B tests and causal inference studies, to evaluate business impact and support data-driven decision-making.
• Establish and improve experimentation frameworks, modeling standards, and best practices across the organization.
• Collaborate with data engineering teams to productionize models through scalable data pipelines, feature stores, and robust deployment processes.
• Translate analytical findings and model outputs into clear business recommendations for product, growth, finance, and leadership stakeholders.
• Identify opportunities to leverage AI and machine learning to improve customer experiences, product performance, and revenue outcomes.
• Ensure responsible use of customer data through privacy-conscious modeling practices and compliance with data governance standards.

• 3+ years of experience building, deploying, and maintaining machine learning models in production environments.
• Strong proficiency in Python and SQL, with hands-on experience using modern machine learning frameworks such as scikit-learn, PyTorch, or TensorFlow.
• Solid understanding of statistics, experimentation methodologies, hypothesis testing, causal inference, and predictive modeling techniques.
• Proven experience working on predictive use cases such as churn prediction, customer lifetime value forecasting, propensity modeling, recommendation systems, or related applications.
• Demonstrated ability to own projects end-to-end, from business problem framing through production deployment and impact measurement.
• Strong communication skills with the ability to explain complex technical concepts and analytical findings to non-technical stakeholders.
• Comfortable working independently and making decisions in fast-changing, high-growth environments.
• Experience collaborating with cross-functional teams across product, engineering, growth, and business functions.
• Familiarity with MLOps practices, feature stores, real-time inference pipelines, or scalable machine learning infrastructure is a plus.
• Experience within B2C SaaS, subscription-based products, marketplaces, or product-led growth environments is highly desirable.
• Knowledge of product analytics platforms such as Amplitude, Mixpanel, or Segment is an advantage.
• Exposure to recommendation systems, NLP, generative AI, or AI-powered product features is considered a plus.

• Fully remote position with the flexibility to work from the Netherlands and across eligible European locations.
• Flexible working hours aligned with European business hours.
• Competitive B2B contract arrangement.
• 22 days of paid time off in addition to public holidays.
• High level of ownership and autonomy with direct influence on product and business strategy.
• Opportunity to build and shape a growing data function from an early stage.
• Exposure to impactful machine learning initiatives with measurable business outcomes.
• Collaborative and entrepreneurial work environment focused on innovation and continuous learning.
• Close partnership with senior stakeholders and cross-functional teams across the organization.
• Opportunity to contribute to the development of AI-driven products and experimentation capabilities.