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Data Scientist – Credit Risk

vor 3 Monaten


Berlin, Berlin, Deutschland ING Deutschland Vollzeit
(Senior) Data Scientist – Credit Risk & Risk Models (w/m/d)

am Standort Berlin

Deine Modelle sorgen dafür, dass unser "risky business" alles andere als das ist? Mit Deiner analytischen Denkweise, durchblickst Du komplexe Sachverhalte nicht nur, Du kannst sie auch verständlich erklären und bewerten? Dabei legst Du genau wie wir Wert auf ein wertschätzendes Miteinander und Kommunikation auf Augenhöhe? Perfekt Bewirb Dich jetzt – Lebenslauf genügt – Dein Team im Centre of Expertise "Credit Risk" freut sich schon auf Dich

Deine Aufgaben
  • Mit Deiner Daten-Expertise entwickelst und verbessert Du unsere Risiko-Scorecards für Kreditentscheidungen und hilfst uns so, unser Risiko niedrig und den Mehrwert für unsere Kund*innen hoch zu halten.
  • Natürlich stellst Du außerdem sicher, dass unsere Kreditmodelle mit Konzernrichtlinien und -anforderungen im Einklang stehen – in der initialen Entwicklung und im Lauf ihres gesamten Lebenszyklus.
  • Deine Adleraugen wachen mittels Monitorings, Bewertung und Reporting sorgfältig über unsere Modelle und ihre Performance.
  • Dabei lenkst Du mit Gap-Analyse, Risiko Assessment und Mitigation alles in die richtigen Bahnen und dank Deiner detaillierten Dokumentation sind unsere Modelle stets zugänglich und verständlich.
  • Teamwork und Kommunikation schreibst Du groß und arbeitest so nicht nur eng und erfolgreich mit anderen Risikomodellfunktionen zusammen, sondern bist auch kompetente Ansprechperson für interne und externe Prüfer sowie Aufsichtsbehörden bei modellbezogenen Fragestellungen.


Dein Profil
  • Master-Abschluss in Statistik, Wirtschaftswissenschaften, Ingenieurwesen, Finanzen, Mathematik oder einem verwandten quantitativen Bereich; eine Promotion ist von Vorteil
  • Berufserfahrung in der Kreditrisikomodellierung / -validierung in Finanzinstituten
  • Praxis in Techniken des Machine Learning, etwa Regression, Klassifizierung, Clustering und Ensemble-Methodik, sowie Kenntnisse in Supervised und Unsupervised Learning und Erfahrung in der Lösung praktischer Probleme mit Machine Learning
  • Know-how in der Modellbildung (Datenbereinigung, Auswahl abhängiger Variablen, Untersuchung und Verständnis unabhängiger Variablen, Variablenreduktion, bivariate Analyse, Variablengruppierung, Erstellung logistischer / linearer Modellbildung, Modellvalidierung usw.)
  • Kenntnisse in Python und anderen analytischen Tools (SQL etc.)
  • Problemlösungs-, Motivations- und Kommunikationsfähigkeiten, gepaart mit Zuverlässigkeit und einer Hands-on Arbeitsweise
  • Fließendes Englisch in Wort und Schrift, Deutschkenntnisse sind von Vorteil
Freu Dich auf zahlreiche Benefits
  • Betriebliche Altersvorsorge, Vermögenswirksame Leistungen, kostenloses Deutschlandticket & Bike LeasING, Betriebsrestaurant
  • Mobiles Arbeiten je nach Position und Abteilung im Rahmen von betrieblichen, regulatorischen und gesetzlichen Anforderungen, individuelle Arbeitszeitmodelle, Sabbatical, Bezuschussung von Pflege- & Kinderbetreuungskosten
  • Eigene Budgets für persönliche Entwicklung und Gesundheit plus persönliches Ausstattungsbudget für Deinen mobilen Arbeitsplatz

Bereit für einen neuen Job?

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