• You will take on a key role, working not only operationally but also strategically reshaping and embedding the Data Science function at Knuddels. • Leadership & team building: As the team is evolving, you will continue to expand its structure and foster your team members’ development through coaching and feedback. • Data strategy & culture: Together with company leadership, you will define the long-term data strategy. Your goal is to establish a genuine data-driven culture, empower colleagues, and make data understandable and accessible across the company. • Sparring partner & bridge builder: You act as the data-driven conscience but do not rely on numbers blindly. You link quantitative analyses with qualitative feedback from the community (e.g., through close exchange with Community Management) to form a holistic view and enable well-founded decisions. • Hands-on Data Science: You work operationally with our complex data (millions of events per day) to extract valuable insights using data mining, clustering, forecasting, recommendation systems, and classification. • Quality & processes: You ensure the correctness of our data across systems (DWH, analytics) and establish best practices (e.g., code reviews, documentation) for scalable data-science products. • Business impact: You derive concrete actions from your analyses that deliver the greatest value to our community and secure the long-term success of Knuddels.

• Own and evolve the end-to-end creator data product strategy • Define and maintain a long-term roadmap that improves creator and audience data • Identify high-leverage data opportunities for Sales, Strategy, and Agency teams • Translate ambiguous business problems into clear data product bets

• Design and develop models to extract entities, detect intents, and understand document structure • Tackle challenges like long-context reasoning, layout-aware NLP, and ambiguous inputs • Evaluate model performance where ground truth is partial, uncertain, or evolving • Shape the roadmap and success metrics for replacing legacy document processing systems with smarter, scalable solutions • Work with other data scientists and engineers to optimize machine learning models and insert them into end-to-end pipelines • Understand product use-cases and define key performance metrics for models according to business requirements • Set up systems for long-term improvement of models and data quality (e.g. active learning, continuous learning systems, etc.)

• Conduct experimentation and execute causal inference analyses on pricing, marketing, and conversion models to drive revenue optimization. • Develop Pricing Optimization algorithms to maximize the unit economics of our lending products while driving meaningful growth in our origination businesses. • Develop and maintain predictive ML models to assess potential risks and opportunities across our lending products, contributing to the enhancement of risk and marketing assessment procedures. • Conceptualize, research, and prototype data-driven solutions, effectively communicating their impact to the stakeholders. • Collaborate closely with cross-functional teams and stakeholders to accelerate solution iteration and achieve measurable outcomes. • Build funnel dashboards and perform root cause analysis to monitor and identify user behavioral patterns and areas of opportunity. • Collaborate with data and infrastructure engineers to deploy ML and Pricing pipelines, from data collection through model deployment. This includes automating training and ongoing monitoring utilizing BI tools. • Prepare technical designs and documentation using git and Confluence.