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Masterand/Masterthesis - Data Scientist (m/w/d)
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Financial Accountant (W/M/D)
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Financial Accountant (W/M/D)
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Financial Accountant (W/M/D)
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Financial Accountant (W/M/D)
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Financial Accountant (W/M/D)
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Financial Accountant (W/M/D)
Warner Bros. DiscoveryWachtbergWelcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes,
Financial Accountant (W/M/D)
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Financial Accountant (W/M/D)
Warner Bros. DiscoveryJülichWelcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes,
Masterand/Masterthesis - Data Scientist (m/w/d)
- Ostfildern, Baden-Württemberg, Germany
- Ostfildern, Baden-Württemberg, Germany
À propos
Tagtäglich stellen wir unser Wissen bereit - stets aktuelle Daten und Informationen rund ums Auto. Wir arbeiten beispielsweise für faire, unabhängig ermittelte Gebrauchtwagen- und Reparaturpreise für alle. Dabei übernimmt jeder Einzelne gerne Verantwortung für seine Aufgaben und: Es macht uns großen Spaß, gemeinsam erfolgreich zu sein. Weltweit entwickeln 550 Mitdenker und Mitdenkerinnen aus 26 Nationen zukunftsweisende IT-Lösungen, die den digitalen Wandel voranbringen.
- Explorative Analyse und Strukturierung großer realer Telematik-Datensätze aus Fahrzeugflotten
- Entwicklung und Bewertung geeigneter Features zur Beschreibung von Batteriezustand und Degradation
- Entwicklung, Anwendung und Vergleich von Machine-Learning- und Zeitreihenmodellen zur SOH-Schätzung
- Untersuchung der Übertragbarkeit von Labor- auf reale Flottendaten (z. B. Transfer Learning)
- Konzeption und Umsetzung von Validierungsstrategien bei fehlender Ground Truth
- Visualisierung und Interpretation von Degradationsverläufen innerhalb der Fahrzeugflotte
- Entwicklung eines prototypischen datengetriebenen Ansatzes zur Batteriezustandsschätzung
- Wissenschaftliche Dokumentation und Bewertung der Ergebnisse
- Fortgeschrittene Studienphase in Informatik, Statistik, Maschinenbau, Physik oder einem verwandten Fachgebiet
- Kenntnisse in Machine Learning, statistischer Modellierung oder Zeitreihenanalyse
- Erfahrung in Python (insbesondere NumPy, pandas, scikit-learn; optional PyTorch/TensorFlow)
- Fähigkeit zur strukturierten Analyse komplexer, realer Datensätze
- Selbstständige, methodisch saubere und lösungsorientierte Arbeitsweise
- Interesse an datengetriebenen Fragestellungen im Kontext Elektromobilität und Fahrzeugtechnik
- Vorteilhaft: Grundkenntnisse in Batterietechnologie oder Telematikdatenanalyse
Compétences linguistiques
- German
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