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Senior Machine Learning Engineer
happyhotel. Develop and optimize forecasting and pricing models and data-driven decision logics .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and optimizing forecasting and pricing models, with a strong focus on data-driven decision-making and model evaluation. Proficient in SQL and Python, with a solid understanding of data quality and reproducible workflows in a business context.
Highest-signal resume keywords
Data Science ExperienceStrong SQL SkillsClean Python CodingModel Evaluation and BacktestingFluent German and Good English Skills
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Forecasting ModelsPricing ModelsTime Series AnalysisData QualityModel EvaluationA/B TestingData Leakage PreventionVersioningAutomation of AnalysesDebugging
Soft Skills
Clear CommunicationReliabilityEntrepreneurial MindsetPragmatic Thinking
Tools & Technologies
SQLPythonDbtSnowflakeMetabaseAWS
Industry Keywords
Revenue ManagementDynamic PricingECommerceTravelMobility
Tech Stack
Tools & technologiesAWSCloudPythonSQL
About the role
Key responsibilities & impact- Develop and optimize forecasting and pricing models and data-driven decision logics
- Work with time series, demand signals, and heterogeneous data sources
- Define features and labels carefully to prevent data leakage
- Evaluate models through backtesting, robust metrics, and segmentation
- Support holdouts and A/B testing logic
- Balance offline and online performance
- Raise standards for backtesting, reproducibility, and versioning
- Enhance dashboards and reports to make model and business KPIs transparent
- Drive reproducible workflows with versioning, clear pipelines, and meaningful tests
- Automate recurring analyses and evaluation runs
- Collaborate closely with Product and Engineering
- Deliver measurable, data-driven improvements in the Pricing & Revenue context
Requirements
What you’ll need- 4+ years of experience in data science or applied ML engineering
- Ideally, experience directly in a product or business context
- Extremely strong SQL skills
- Deep understanding of data quality, debugging, and consistent metrics
- Clean Python coding and transparent analyses
- Basic knowledge of bias and leakage awareness
- Ability to think in guardrails and offline-versus-online scenarios
- Full ownership of topics
- Pragmatic application of the 80/20 principle
- Reliability and clear communication
- Entrepreneurial mindset
- Fluent German and good English skills
- Nice to have: experience in revenue management or dynamic pricing, such as hotel, travel, eCommerce, or mobility
- Nice to have: familiarity with seasonality, events, lead times, and segment patterns
- Nice to have: experience with analytics engineering or warehouse tools such as dbt, Snowflake, or Metabase
- Bonus: hands-on MLOps tooling and cloud infrastructure skills, such as AWS
Benefits
Comp & perks- Remote within Germany option with office attendance twice per quarter for three days each time
- Hybrid option with two days a week in the office
- Custom work arrangement option
- Opportunity to work on impactful product improvements in forecasting, pricing, and product insights