Your RoleAs a Senior Machine Learning Engineer, you will work in the Pricing & Revenue context, focusing on data-driven improvements for forecasting, pricing logic, and product insights.
You will develop analyses and models that demonstrate measurable impact in our product – with thorough evaluation, a solid data foundation, and pragmatic implementation.
You will collaborate closely with Product & Engineering.
Your ResponsibilitiesModel Evolution: You will develop and optimize our forecasting and pricing models as well as data-driven decision logics, always with methodical pragmatism and a strong focus on impact.
Signal Hunting: You will work with time series, demand signals, and heterogeneous data sources.
You define features and labels carefully to leave no chance for leakage.
Measurement & Guardrails: You are responsible for evaluation through backtesting, robust metrics, and segmentation.
You support holdouts and A/B logics and maintain the balance between offline and online performance.
ML Engineering Best Practices: You raise standards for backtesting, reproducibility, and versioning.
For us, it's: Engineering quality instead of notebook-only.
Data Visibility: You enhance dashboards and reports that make model and business KPIs transparent.
Your focus is always on the highest data quality.
Smart Workflows: You drive reproducible workflows (versioning, clear pipelines, meaningful tests) and automate recurring analyses and evaluation runs.
Your ProfileTrack Record: You have 4+ years of experience in data science or applied ML engineering – ideally directly in a product or business context.
Data Intuition: You possess extremely strong SQL.
Initial experience with product-oriented setups is a big plus.
Experiment Mindset: You master the basics of bias/leakage-awareness and know how to think in guardrails and offline-vs-onlin.