Senior Machine Learning Engineer (m/f/d)

Meyandy LLC; Offenburg; Hybrid; EUR 90.000 - 120.000; Vollzeit

Zusammenfassung

Meyandy LLC is seeking a Senior Machine Learning Engineer to join our Pricing & Revenue team in Germany. You will evolve forecasting and pricing models, hunt signals in time-series data, and design guardrails for offline and online evaluation.

You will build robust analytics pipelines and dashboards to reveal product KPIs and business impact. Ideal candidates have 4+ years in data science or ML engineering, strong SQL, Python, and German language skills, with an entrepreneurial, ownership-driven

Qualifikationen

• 4+ years of experience in data science or applied ML engineering in a product/business context.
• Strong SQL skills and data quality mindset.
• Clean Python code and transparent analyses.
• Experience with bias/leakage awareness and offline/online guardrails.
• Ownership mentality and pragmatic, 80/20-driven work style.
• Fluent in German; good English skills.

Aufgaben

• Model evolution for forecasting and pricing models with measurable impact.
• Signal hunting with time series, demand signals, and heterogeneous data sources.
• Define features and labels to prevent leakage.
• Elevate backtesting, robust metrics, and segmentation.
• Raise ML engineering standards: reproducibility, versioning, and testing.
• Improve dashboards and reporting for KPIs; ensure data quality.
• Drive reproducible workflows and automation of analyses.

Kenntnisse

SQL skills

Python proficiency

Experiment mindset

Ownership

German language

Tools

dbt

Snowflake

MLOps tools

Jobbeschreibung

## **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