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happyhotel

Senior Machine Learning Engineer (m/f/d)

happyhotel Offenburg, Baden-Württemberg, Germany

Software Development · 11-50 employees

20 h ago
Remote machine-learning Mid (2-5 yrs) Full-time Germany
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About the role

You will develop and optimize forecasting and pricing models while ensuring high data quality and robust evaluation metrics. Additionally, you will collaborate with product and engineering teams to implement reproducible workflows and automated data-driven decision logics.

What they look for

Machine Learning Python SQL Data Science Forecasting Pricing Models Time Series Analysis Backtesting A/B Testing Data Quality MLOps Cloud Infrastructure AWS Data Visualization Reproducibility Revenue Management

Requirements

The ideal candidate has 4+ years of experience in data science or applied machine learning with strong proficiency in Python and SQL. You should possess a pragmatic experiment mindset and experience with product-oriented data setups.

Full description

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 are fluent in German and have good English skills.

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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