📍 Job Overview

Job Title: Product Owner (m/w/d) - Data Science, AI, Cloud
Company: codemanufaktur GmbH
Location: Erlangen, Bavaria, Germany
Job Type: Full-time
Category: Product Management, Data Science, AI, Cloud
Date Posted: 2025-07-30
Experience Level: 5-10 years
Remote Status: On-site

🚀 Role Summary

Key Responsibilities: Steer, coordinate, and manage software projects based on customer requirements, translate customer needs into product ideas, and lead a team of Data Scientists and Software Developers.
Key Skills: Product ownership, data science, AI, software development, team leadership, project management, Android development, cloud architecture, agile methodologies, Scrum, communication skills, technical understanding, problem-solving, planning skills, German, English.

📝 Enhancement Note: This role requires a strong technical background and experience in leading development teams to successfully manage projects and translate customer needs into innovative data-driven solutions.

💻 Primary Responsibilities

Project Management: Steer, coordinate, and manage software projects based on customer requirements, ensuring project goals are met and customer expectations are exceeded.
Product Ownership: Translate customer needs into product ideas and features, and maintain the product backlog.
Team Leadership: Lead a team of Data Scientists and Software Developers, fostering a collaborative and innovative work environment.
Stakeholder Communication: Communicate project progress, risks, and issues to stakeholders, ensuring all parties are informed and aligned.
Technical Expertise: Contribute to technical discussions and decisions, leveraging your expertise in data science, AI, and cloud architecture.

📝 Enhancement Note: This role requires a balance of strong technical skills and leadership abilities to effectively manage projects, teams, and stakeholder communications.

🎓 Skills & Qualifications

Education: A completed technical degree in a relevant field, such as Computer Science, Data Science, or a related discipline.

Experience: At least 5-10 years of experience in leading development teams, project management, and software development, with a strong focus on data science, AI, and cloud architecture.

Required Skills:

Proven experience in leading development teams and managing projects
Strong technical background in data science, AI, and cloud architecture (Azure, AWS)
Experience in Android development, ideally in the automotive field
Excellent communication skills in German and English
Strong problem-solving skills and planning abilities
Familiarity with agile methodologies (Scrum) and tools (Atlassian Jira, Confluence)

Preferred Skills:

Experience with Large Language Models (LLM), Speech-to-Text, Text-to-Speech, and Speech2Speech or RAG
Knowledge of the automotive industry and its specific requirements
Familiarity with modern cloud architecture and tooling

📝 Enhancement Note: This role requires a unique blend of technical expertise, leadership skills, and industry-specific knowledge to effectively manage projects and teams in the data science and AI domain.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

A well-structured and up-to-date portfolio showcasing your experience in data science, AI, and cloud architecture projects.
Examples of successful project management and team leadership, highlighting your ability to deliver results and drive innovation.
Demonstrations of your technical expertise, such as code samples, architecture diagrams, or data visualizations.

Technical Documentation:

Detailed project documentation, including project charters, requirements specifications, and test cases.
Code comments and documentation, demonstrating your attention to detail and commitment to maintainable code.
Version control history and deployment processes, showcasing your understanding of software development best practices.

📝 Enhancement Note: As a Product Owner, your portfolio should emphasize your ability to manage projects, lead teams, and drive data-driven innovation, while also demonstrating your technical expertise in data science, AI, and cloud architecture.

💵 Compensation & Benefits

Salary Range: €70,000 - €90,000 per year (based on experience and qualifications)

Benefits:

Careful onboarding to ensure a smooth transition into the team
33 days of annual leave to promote work-life balance
Targeted professional development opportunities to support your career growth
Company bicycle, public transport ticket, or parking space to facilitate your commute
Excellent public transport connections and a family-friendly company culture
Premium gym subsidy to support your health and well-being
Free drinks, barista coffee, ice cream, and fruit to enjoy at the office

Working Hours: Full-time (40 hours per week), with flexible working hours and the possibility of remote work for specific tasks or projects.

📝 Enhancement Note: The salary range is estimated based on market research for similar roles in the data science and AI domain in the Erlangen area. Benefits are tailored to support work-life balance, professional development, and employee well-being.

🎯 Team & Company Context

🏢 Company Culture

Industry: Software development and data science, with a focus on complex individual software and AI-driven solutions.

Company Size: Medium-sized (50-249 employees), fostering a collaborative and innovative work environment.

Founded: 2008, with a strong focus on growth and expansion in the data science and AI domain.

Team Structure:

A dedicated data science team, working on cutting-edge projects in various industries.
Close collaboration with software development teams, ensuring seamless integration of data-driven solutions into software products.
Cross-functional teams, involving designers, marketers, and business stakeholders to drive user-centric innovation.

Development Methodology:

Agile/Scrum methodologies, with a focus on iterative development and continuous improvement.
Code reviews, testing, and quality assurance practices to ensure high-quality software products.
Deployment strategies, CI/CD pipelines, and server management to support efficient and reliable software development processes.

Company Website: codemanufaktur.com

📝 Enhancement Note: The company's focus on growth and expansion in the data science and AI domain creates exciting opportunities for professionals looking to drive innovation and make a significant impact in their role.

📈 Career & Growth Analysis

Web Technology Career Level: Senior Product Owner, responsible for managing projects, leading teams, and driving data-driven innovation in the data science and AI domain.

Reporting Structure: Reports directly to the management team, with a high level of autonomy and decision-making authority.

Technical Impact: Plays a crucial role in defining the product vision, managing project timelines, and ensuring the delivery of high-quality data-driven solutions that meet customer expectations.

Growth Opportunities:

Technical Growth: Expand your expertise in data science, AI, and cloud architecture, and stay up-to-date with the latest trends and best practices in the industry.
Leadership Growth: Develop your leadership skills and take on more responsibilities within the team or across multiple projects.
Mentoring & Knowledge Sharing: Share your expertise with junior team members and contribute to their professional development.

📝 Enhancement Note: This role offers significant growth opportunities for professionals looking to advance their careers in data science, AI, and cloud architecture, while also developing their leadership and management skills.

🌐 Work Environment

Office Type: Modern, collaborative workspaces designed to foster innovation and creativity.

Office Location(s): Erlangen, Bavaria, Germany, with excellent public transport connections and a family-friendly company culture.

Workspace Context:

Collaborative workspaces, encouraging cross-functional team interaction and knowledge sharing.
Access to multiple monitors, testing devices, and development tools to support efficient and effective software development.
A strong focus on work-life balance, with flexible working hours and remote work options for specific tasks or projects.

Work Schedule: Full-time (40 hours per week), with flexible working hours and the possibility of remote work for specific tasks or projects.

📝 Enhancement Note: The company's focus on collaboration, innovation, and work-life balance creates an engaging and supportive work environment for professionals looking to drive data-driven solutions and make a significant impact in their role.

📄 Application & Technical Interview Process

Interview Process:

Initial Screening: A brief phone or video call to discuss your application, experience, and career goals.
Technical Assessment: A hands-on technical assessment, focusing on your data science, AI, and cloud architecture skills, as well as your problem-solving abilities.
Behavioral Interview: A structured interview focusing on your leadership, communication, and teamwork skills, as well as your ability to manage projects and stakeholders.
Final Decision: A final decision based on your technical skills, cultural fit, and alignment with the company's values and goals.

Portfolio Review Tips:

Highlight your experience in data science, AI, and cloud architecture projects, emphasizing your technical expertise and leadership skills.
Showcase your ability to manage projects, lead teams, and drive data-driven innovation, using concrete examples and success stories.
Demonstrate your understanding of the automotive industry and its specific requirements, if applicable.

Technical Challenge Preparation:

Brush up on your data science, AI, and cloud architecture skills, focusing on the latest trends and best practices in the industry.
Prepare for hands-on technical assessments, focusing on problem-solving, code quality, and architecture decision-making.
Familiarize yourself with the company's technology stack and development methodologies, ensuring a strong fit with the team and its goals.

ATS Keywords: Data Science, AI, Cloud Architecture, Product Ownership, Project Management, Team Leadership, Agile Methodologies, Scrum, Android Development, Cloud Architecture, Azure, AWS, German, English, Communication Skills, Technical Understanding, Problem Solving, Planning Skills.

📝 Enhancement Note: The interview process is designed to assess your technical skills, leadership abilities, and cultural fit, ensuring a strong match with the company's values and goals in the data science and AI domain.

🛠 Technology Stack & Web Infrastructure

Data Science & AI Technologies:

Programming Languages: Python, R, SQL
Libraries & Frameworks: TensorFlow, PyTorch, Scikit-learn, Keras, Pandas, NumPy, Matplotlib, Seaborn
Cloud Platforms: AWS, Azure, GCP
Databases: PostgreSQL, MySQL, MongoDB, Redis
Big Data Tools: Hadoop, Spark, Hive, Pig, Kafka

Cloud Architecture & Infrastructure:

Infrastructure as Code (IaC) Tools: Terraform, CloudFormation, Azure Resource Manager (ARM)
Containerization & Orchestration: Docker, Kubernetes, Amazon ECS, Azure AKS
Serverless Platforms: AWS Lambda, Azure Functions, Google Cloud Functions
Monitoring & Logging: Prometheus, Grafana, ELK Stack, Datadog, New Relic
CI/CD Pipelines: Jenkins, GitLab CI/CD, CircleCI, GitHub Actions

📝 Enhancement Note: The company's technology stack is designed to support cutting-edge data science, AI, and cloud architecture projects, with a strong focus on innovation, efficiency, and scalability.

👥 Team Culture & Values

Data Science & AI Values:

Innovation: Foster a culture of continuous learning and experimentation, driving data-driven innovation and pushing the boundaries of what's possible.
Collaboration: Encourage cross-functional teamwork and knowledge sharing, leveraging the collective expertise of the team to deliver exceptional results.
Quality: Maintain a strong focus on code quality, architecture decision-making, and performance optimization, ensuring high-quality data-driven solutions.
Customer Focus: Prioritize customer needs and expectations, ensuring data-driven solutions meet their unique requirements and exceed their expectations.

Collaboration Style:

Cross-functional Integration: Work closely with software development teams, designers, marketers, and business stakeholders to drive user-centric innovation and deliver exceptional data-driven solutions.
Code Review Culture: Encourage peer-to-peer code reviews and knowledge sharing, ensuring high-quality code and efficient problem-solving.
Knowledge Sharing: Foster a culture of continuous learning and development, with regular workshops, training sessions, and brown bag lunches.

📝 Enhancement Note: The company's data science and AI values are designed to foster a collaborative, innovative, and customer-focused work environment, driving data-driven solutions that meet the unique needs and expectations of its customers.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Data Quality & Management: Develop and implement robust data quality and management strategies, ensuring accurate and reliable data-driven solutions.
Model Deployment & Scalability: Design and implement scalable and efficient deployment strategies for data-driven models and solutions.
User Experience & Accessibility: Ensure data-driven solutions meet user expectations and accessibility standards, with a strong focus on user-centric design and intuitive interfaces.
Emerging Technologies: Stay up-to-date with the latest trends and best practices in data science, AI, and cloud architecture, and leverage emerging technologies to drive innovation and competitive advantage.

Learning & Development Opportunities:

Technical Skill Development: Expand your expertise in data science, AI, and cloud architecture, with a strong focus on emerging technologies and best practices in the industry.
Conference Attendance & Certification: Attend industry conferences, workshops, and training sessions, and pursue relevant certifications to support your professional development.
Mentoring & Leadership Development: Participate in mentoring programs and leadership development initiatives, fostering your growth as a technical expert and leader in the data science and AI domain.

📝 Enhancement Note: The company's technical challenges and learning opportunities are designed to drive data-driven innovation, foster professional development, and create a competitive advantage in the data science and AI domain.

💡 Interview Preparation

Technical Questions:

Data Science & AI Fundamentals: Demonstrate your understanding of data science and AI fundamentals, with a strong focus on problem-solving, data manipulation, and model selection.
Cloud Architecture & Performance: Showcase your expertise in cloud architecture and performance optimization, with a strong focus on scalable and efficient deployment strategies.
Problem-Solving & Debugging: Demonstrate your ability to identify, diagnose, and resolve technical issues, with a strong focus on efficient problem-solving and code quality.

Company & Culture Questions:

Data Science & AI Culture: Demonstrate your understanding of the company's data science and AI values, with a strong focus on innovation, collaboration, and customer focus.
Agile Methodologies & Collaboration: Showcase your familiarity with agile methodologies, Scrum, and cross-functional teamwork, with a strong focus on driving user-centric innovation and delivering exceptional results.
User Experience & Impact: Demonstrate your ability to assess and measure the impact of data-driven solutions on user experience, with a strong focus on performance metrics and optimization techniques.

Portfolio Presentation Strategy:

Live Website Demonstration: Present your data science, AI, and cloud architecture projects using live website demonstrations, highlighting your technical expertise and leadership skills.
Code Explanation & Architecture Decision Reasoning: Walk through your code and architecture decisions, demonstrating your understanding of data science, AI, and cloud architecture best practices.
User Experience Showcase: Highlight the user experience aspects of your data-driven solutions, with a strong focus on accessibility, performance, and intuitive interfaces.

📝 Enhancement Note: The interview process is designed to assess your technical skills, leadership abilities, and cultural fit, ensuring a strong match with the company's values and goals in the data science and AI domain.

📌 Application Steps

To apply for this Product Owner (m/w/d) - Data Science, AI, Cloud position at codemanufaktur GmbH:

Submit Your Application: Visit the application link and submit your application, including your resume, cover letter, and portfolio.
Prepare Your Portfolio: Tailor your portfolio to showcase your experience in data science, AI, and cloud architecture projects, emphasizing your technical expertise and leadership skills.
Optimize Your Resume: Highlight your relevant experience, skills, and achievements in data science, AI, and cloud architecture, using relevant keywords and industry-specific terminology.
Research the Company: Familiarize yourself with the company's technology stack, development methodologies, and data science and AI values, ensuring a strong fit with the team and its goals.
Prepare for Technical Interviews: Brush up on your data science, AI, and cloud architecture skills, focusing on problem-solving, code quality, and architecture decision-making.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and data science, AI, and cloud architecture industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Product Owner (m/w/d) - Data Science, AI, Cloud