Impress employers and recruiters.
Choose from hundreds of resume examples.

Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

About the Role

We are seeking a Data Scientist to join our interdisciplinary team, driving challenging Data Science projects and developing effective, data-driven solutions for our clients. You will extract key data, create innovative solutions using modern methods, and collaborate closely with clients and the Data Engineering team.

Responsibilities

• Design and lead challenging Data Science projects in an interdisciplinary team.
• Identify client needs and develop effective, data-driven solutions.
• Extract crucial data from client datasets for task-specific purposes.
• Create innovative solutions using statistics, machine learning, mathematical optimization, and visual analytics.
• Collaborate closely with your Tribe Lead.
• Communicate results to clients and support the implementation of ideas with the Data Engineering team.
• Participate in client meetings as an expert.

Requirements

• Completed degree in Computer Science, Data Science, Mathematics, or a data-driven field.
• Fluent German and English language skills (written and spoken).
• Strong analytical skills and the ability to communicate complex technical concepts clearly.
• Out-of-the-box thinking.
• High commitment to continuous learning and exploring new tools and technologies.
• Minimum 5 years of project experience in the Data field, preferably in a consulting firm.
• Minimum 3 years of practical experience with Cloud technologies (Azure, AWS).
• Very good knowledge of Software Development (Python, object-oriented).
• Practical experience in Data Science areas such as LLMs/NLP (e.g., Transformer, Conversational AI) or Computer Vision (e.g., Stable Diffusion, OCR).

Skills

• Data Science
• Machine Learning
• Statistics
• Mathematical Optimization
• Visual Analytics
• Python
• Object-Oriented Programming
• Cloud Technologies (Azure, AWS)
• LLMs/NLP
• Transformer
• Conversational AI
• Computer Vision
• Stable Diffusion
• OCR

Location

• Munich
• Nuremberg
• Leipzig
• Berlin
• Frankfurt am Main
• Essen

Work Type

• Hybrid
• Workation (EU)

Experience Level

• Minimum 5 years of project experience in the Data field
• Minimum 3 years of practical experience with Cloud technologies

Education Level

• Completed degree in Computer Science, Data Science, Mathematics, or a data-driven field.

Benefits

• Trust-based working hours with flexible scheduling
• Workation option (work from EU countries)
• Unique team atmosphere
• Flat hierarchies
• Open feedback culture
• Annual team workshops
• Buddy program
• Regular social and professional events
• Dog-friendly offices
• Intensive onboarding and integration process
• Personal development plan
• Individual further training opportunities
• Diverse workshop and training offerings within the Data.Academy
• Leadership, project management, and expert career paths
• Childcare subsidy
• Company pension plan with 20% subsidy
• Numerous corporate benefits and employee offers
• Starting credit in the internal merchandise shop
• Competitive salary with variable components
• Mental Health & Wellbeing Support, coaching, and meditation
• Fitness and yoga rooms
• Regular employee surveys
• EGYM Well Pass membership
• Bicycle leasing
• Internal sports activity groups
• Free hot and refreshing drinks
• Fresh fruit in the office
• Rooftop terrace (grill)
• Subsidy for the Deutschlandticket
• Central office locations
• Good public transport connections

About the Company

• Alexander Thamm GmbH is a leading provider of Data Science and Artificial Intelligence in German-speaking countries.
• The company generates real added value from data for and with its customers to ensure their future competitiveness.
• Alexander Thamm GmbH develops and implements data-driven innovations and business models.
• The service portfolio covers the entire Data Journey: from data strategy, algorithm development, and IT architecture setup to maintenance and operation.
• Follow us on Facebook, Instagram, LinkedIn, or Stackoverflow to learn more and look behind the scenes.