Senior Machine Learning Engineer (m/f/d)

Happyhotel; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

happyhotel is seeking a Senior Machine Learning Engineer to join the Pricing & Revenue team in the United States. You will develop data-driven forecasting and pricing logic, create insights, and collaborate with Product & Engineering to drive measurable product impact.

You will evolve forecasting models, define features from time-series signals, and ensure robust evaluation with backtesting and guardrails. A strong data foundation and reproducible workflows are essential.

Qualifications

• 4+ years of experience in data science or applied ML engineering, ideally in a product context.
• Strong SQL skills and a deep sense for data quality and metrics.
• Proficient Python coding with transparent analyses; product-oriented setup a plus.
• Fluent in German with good English skills.
• Ownership mindset and ability to work pragmatically (80/20).
• Entrepreneurial spirit and willingness to make a difference.

Responsibilities

• Model evolution: develop and optimize forecasting and pricing models with measurable impact.
• Signal hunting: work with time series, demand signals, and heterogeneous data.
• Measurement & guardrails: evaluate with backtesting, robust metrics, segmentation; support A/B logic.
• ML engineering best practices: improve backtesting, reproducibility, and versioning.
• Data visibility: improve dashboards and reports for KPI transparency.
• Smart workflows: drive reproducible pipelines and automate analyses.

Skills

SQL

Python

Experimentation

Ownership

Communication

Tools

dbt

Snowflake

MLOps

AWS

Job 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