4 beste Stellen als machine learning in kehl – aktuell auf Personalsuche

Staff Machine Learning Engineer - Pricing & Revenue (m/f/d)
happyhotel —Offenburg
- Vollzeit
- Homeoffice
- Master
Direkt bewerben
Staff Machine Learning Engineer - Pricing & Revenue (m/w/d)
happyhotel —Offenburg
- Vollzeit
- Homeoffice
- Englisch
- SQL
- Machine Learning
Direkt bewerben
Quereinstieg als Prompt Engineer (m/w/d) – 100% remote
mycareernow GmbH —Offenburg
- Ab 50.000 € pro Jahr
- Teilzeit
- Homeoffice
- Microsoft Word
- Weiterbildungsprogramme
Direkt bewerben
Bachelorthesis im Service Bereich "Entwicklung eines Konzepts zur Anwendung von KI im Aftersales Geschäftsbereich"
HOBART GmbH —Offenburg
- Machine Learning
- Softwareentwicklung
5 Tage

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Staff Machine Learning Engineer - Pricing & Revenue (m/f/d)
happyhotel —Offenburg
You will take on technical leadership and end-to-end ownership for our Pricing/Revenue-ML topics—with a clear focus on measurable impact.
Direkt bewerben
AI-Engineer (m/w/d)
Vollblutwerber GmbH —Lahr
Abgeschlossenes Studium in Informatik, Data Science, oder einem ähnlichen Bereich. Fundierte Kenntnisse in Machine Learning und Deep Learning.

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Staff Machine Learning Engineer - Pricing & Revenue (m/f/d)

happyhotel -
Offenburg

Direkt bewerben

Details zur Stelle

Vollzeit

Qualifikationen

Master

Vollständige Stellenbeschreibung

Your Role

You will take on technical leadership and end-to-end ownership for our Pricing/Revenue-ML topics—with a clear focus on measurable impact. You will work closely with Product and Engineering, define measurability/experiments, and ensure that our models not only “look good” but also perform reliably in practice.

Important: No disciplinary personnel responsibility. You lead through expertise, standards, and ownership.

Your Responsibilities

End-to-End Ownership: You are responsible for the entire lifecycle of pricing and revenue topics—from hypothesis to implementation to measurable evaluation. Your focus: Clear business uplift.
Smart Modeling: You develop and optimize forecasting and pricing models. You pragmatically decide which method gets us to the goal fastest and most stably.
Signal Expertise: You manage time series, demand signals, and heterogeneous data sources. You ensure that features and labels are defined absolutely clean and “leakage-proof.”
Experimentation Framework: You build a robust measurement system (holdouts, A/B tests, guardrails) and define crystal-clear criteria for rollout decisions.
Engineering-Grade ML: You establish standards for backtesting, reproducibility, and versioning. For us, it's: Engineering quality instead of notebook-only.
Reliable Operations: You ensure operations through smart monitoring, drift detection, and pragmatic retraining mechanisms.
Automation & Scale: You automate high-leverage processes (backtests, monitoring checks) to massively increase throughput and quality.
Data Foundation: Where it makes sense, you design data models directly in the warehouse (Snowflake/dbt) as a basis for reliable metrics and features.
Full Transparency: You standardize dashboards (e.g., Metabase) for our business KPIs and ensure the data quality is beyond reproach.
Stakeholder Sparring: You prioritize requirements together with Product & Revenue and translate them into ML solutions. Your motto: Impact over output.

Your Profile

Deep Experience: You have 5+ years relevant experience in ML Engineering, Data Science, or Analytics (or an equivalent track record that convinces us).
Proven Impact: You have already achieved demonstrable success in the areas of pricing, revenue, forecasting, or similar “money systems.”
Evaluation Pro: You think offline vs. online, immediately recognize bias/leakage, and master the fundamentals of robust metrics and guardrails.
Tech Stack: Your Python and SQL skills are production-level (testable, versioned, reproducible).
Startup DNA: You love the 80/20 principle, work extremely pragmatically, and want full ownership for your topics.
Language Skills: You communicate fluently and confidently in English.

Bonus Points (Nice-to-haves)

Domain Knowledge: Experience in revenue management or dynamic pricing (e.g., travel, mobility, eCommerce).
Demand Understanding: You know how seasonality, events, and lead times affect pricing.
Modern Toolchain: You are proficient in analytics engineering (dbt, Snowflake, Metabase) and know how to build a clean data foundation.

Direkt bewerben

Erweiterte Suche

machine learning Jobs in kehl

Staff Machine Learning Engineer - Pricing & Revenue (m/f/d)

Staff Machine Learning Engineer - Pricing & Revenue (m/w/d)

Quereinstieg als Prompt Engineer (m/w/d) – 100% remote

Bachelorthesis im Service Bereich "Entwicklung eines Konzepts zur Anwendung von KI im Aftersales Geschäftsbereich"

Discover related jobs

Ich möchte aktuelle Job-E-Mails für Stellen als machine learning in kehl erhalten

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