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Salary
$88k – $162k per year (Estimated)
Location
Remote (Offenburg, Germany)
Seniority
Senior · 4+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Are you looking for effective revenue management for your hotel? Achieve up to 30% increase in revenue with happyhotel with dynamic pricing.

Your Role

As 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 Responsibilities

  • Model 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 Profile

  • Track 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 skills and a deep sense for data quality, debugging, and consistent metrics.

  • Python Pro: Your Python code is clean and your analyses are transparent. 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-online scenarios.

  • Work Style: You take full ownership of your topics. You work according to the 80/20 principle (pragmatic!), are reliable, and communicate clearly.

  • Entrepreneurial Spirit: You think entrepreneurially and want to truly make a difference.

  • Language Skills: You communicate fluently and confidently in English.

Nice-to-haves - What Sets the Best Apart

  • Domain Expertise: You already have experience in revenue management or dynamic pricing (e.g., hotel, travel, eCommerce, or mobility).

  • Demand Knowledge: You are familiar with seasonality, events, lead times, and segment patterns.

  • Modern Stack: You have already worked with analytics engineering or warehouse tools such as dbt, Snowflake, or Met

  • Hands-On MLOps & Cloud: Bonus if you have hands-on skills to work with MLOps tooling and cloud infrastructure, e.g. AWS

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