Data Scientist (m/f/d)

TN Germany; Herzogenaurach; Vor Ort; EUR 60.000 - 100.000; Vollzeit

Zusammenfassung

Ein innovatives Unternehmen sucht einen erfahrenen Data Scientist, der die Entwicklung fortgeschrittener Analysemethoden vorantreibt. In dieser spannenden Rolle unterstützen Sie den gesamten Analysezyklus, von der Identifizierung geschäftlicher Bedürfnisse bis zur Operationalisierung von Modellen. Sie werden Teil eines dynamischen Teams, das sich auf die Verbesserung der Kundenerfahrung konzentriert, indem es Einblicke generiert und personalisierte Empfehlungen bereitstellt. Ihre Fähigkeiten in Statistik und maschinellem Lernen sind entscheidend, um die Standards zu erhöhen und schnellere Ergebnisse zu liefern. Wenn Sie leidenschaftlich an Daten interessiert sind und gerne in einem internationalen Umfeld arbeiten, ist dies die perfekte Gelegenheit für Sie.

Qualifikationen

• 5+ Jahre Erfahrung in der Analyse in digitalen/eCommerce-Umgebungen.
• Erfahrung in der Entwicklung von Kundensegmentierungen und Modellen.

Aufgaben

• Durchführung von fortgeschrittenen Modellierungen zur Optimierung der Kundenakquise.
• Präsentation von Analyseergebnissen und Erkenntnissen an Kollegen.

Kenntnisse

Statistik

Datenanalyse

Maschinelles Lernen

Kommunikationsfähigkeiten

Teamarbeit

Ausbildung

M.Sc. oder PhD in einem numerischen/statistischen Fach

Tools

NoSQL-Datenbanken

Jobbeschreibung

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As a Data Scientist, you support the development of a defined area of data science topics across the full analytics cycle: from framing business needs, through data exploration and modeling, to operationalization. You execute advanced modeling techniques to create segmentations and generate consumer insights. Your team is key to enabling personalization across all touchpoints and funnels.

Key Responsibilities

• Scope: Execution of advanced modeling in specific data science areas

• Data Science
• Contribute to the development and application of defined advanced analysis methodologies to optimize customer acquisition, engagement, conversion, experience, and loyalty. This includes framing business needs, exploring data, and performing descriptive, predictive, and prescriptive modeling.
• Generate insights to enhance understanding of adidas consumers, exploring their affinities and intents, to make personalized recommendations through the right digital channels at the right time.
• Continuously improve methodologies, challenge the status quo, and raise standards for faster delivery.
• Support the automation and enhancement of the data science platform and machine learning pipeline for real-time use cases.
• Data Science Network & Storytelling
• Prepare coaching sessions on analytic techniques, data science, data engineering, governance, and software development.
• Present analysis results and insights clearly to colleagues at all levels to demonstrate value and facilitate application.
• Support development of customer segmentation, acquisition and retention strategies, predictive models, customer lifetime value metrics, and marketing effectiveness measures.
• „If required“ Responsibilities
• Product Ownership
• Define product vision, roadmap, and user stories for data products.
• Prioritize backlog items, define the definition of done with the product team.
• Build actionable insights iteratively, adhering to data science standards.
• Manage stakeholder relationships.
• Key Relationships:
• Digital Analytics Team
• Business Units (BUs)
• Markets

Requirements

• Education & Professional Experience
• University degree in a numeric/statistical discipline (M.Sc. or PhD)
• 5+ years of analytics experience in digital/eCommerce environments, with strong industry knowledge
• 3+ years in an international, cross-functional setting
• Experience managing a team is a plus

• Soft Skills
• Excellent communication skills, comfortable presenting complex topics at various organizational levels
• Interpersonal and leadership skills
• Proven team player capable of cross-functional collaboration

• Hard Skills
• Strong knowledge of statistics, data mining, machine learning algorithms
• Experience with NoSQL databases
• Experience in data aggregation, modeling, and operationalization of algorithms
• Experience developing customer profiles, CLTV, attribution models, lookalike modeling, clustering, classification, and segmentation on large datasets
• Fluent in English, both verbal and written