Head of Data & AI

Role overview

This opportunity is presented on behalf of a partner employer that handles all applications and follow-up steps. The partner is seeking a Head of Data & AI in Germany to guide the strategy and delivery of a unified data function spanning data engineering, data science, artificial intelligence, quantitative analytics, and business intelligence.

In this senior leadership position, you will define scalable data foundations, advance AI-driven innovation, and develop strong teams that convert complex information into tangible business impact. The role sits at the crossroads of engineering, analytics, and emerging AI capabilities, with responsibility for technical direction, operating standards, and collaboration with senior business leaders in a fast-moving, innovation-led environment.

Key responsibilities

• Set the direction for the Data & AI function and translate long-term business goals into an actionable strategy across engineering, analytics, quantitative research, and AI.
• Lead, coach, and grow multidisciplinary technical teams while putting in place standards, development pathways, and a culture of teamwork and continuous improvement.
• Architect and improve secure, dependable, and scalable data platforms, including ETL/ELT flows, streaming data pipelines, and cloud infrastructure.
• Champion the design and rollout of AI and large language model solutions such as retrieval-augmented generation, AI agents, intelligent automation, and semantic search.
• Establish operating practices for Data Engineering, MLOps, and LLMOps, including CI/CD, version control for models, monitoring, observability, prompt handling, and evaluation processes.
• Maintain strong standards for data quality, governance, privacy, compliance, and responsible AI, with attention to fairness, interpretability, and regulatory requirements.
• Work with senior stakeholders to turn strategic business challenges into data-led solutions, including executive reporting, advanced analytics, experimentation, and measurable outcomes.
• Make informed choices on technology stack, infrastructure performance, and cloud consumption while ensuring the platform remains efficient and scalable.

Requirements

• At least 7 years of practical experience across data engineering, data science, machine learning, quantitative analytics, and data analytics, with ownership of end-to-end solutions.
• Minimum 3 years in a leadership role managing technical data teams and supporting organizational growth.
• A bachelor’s or master’s degree in Computer Science, Engineering, Mathematics, Physics, or another quantitative field.
• Strong Python programming ability and experience delivering production-ready data and machine learning applications.
• Solid grounding in software engineering practices such as CI/CD, testing, clean architecture, code reviews, and DevOps principles.
• Hands-on experience with machine learning methods, statistical modeling, quantitative analysis, and tools such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Deep experience with SQL, analytical databases, OLAP systems, and contemporary data platform architectures.
• Proven capability in shaping AI strategy, building LLM-based applications, and working with vector databases, embeddings, and AI governance frameworks.
• Strong communication, stakeholder management, and leadership skills, with the ability to align technical work to commercial priorities.
• Professional-level English is required.
• Experience in fintech, trading, fraud detection, risk modeling, portfolio analytics, or enterprise LLM integration is an added advantage.

Benefits

• Fully remote role with flexible working arrangements.
• Competitive compensation package.
• 20 days of paid vacation each year.
• 10 days of paid sick leave.
• Public holidays observed according to local law.
• Comprehensive medical insurance coverage.
• Annual budget for professional development and education.
• Allowance for language learning.
• Wellness budget that can be used for gym memberships, sports equipment, and similar health-related expenses.
• The chance to influence the direction and growth of a Data & AI organization while working with modern technology and advanced AI solutions.

Application and privacy information

The partner company manages the hiring process and makes the final decisions, including interviews and assessments. Applications are screened through an AI-assisted matching process designed to review candidates quickly and consistently against the role’s main requirements.

By submitting an application, candidates agree that personal data may be processed to evaluate suitability and shared with the hiring employer under applicable data protection laws, including GDPR. Applicants may exercise their rights to access, correct, delete, or object to processing at any time.

AI tools may be used to support parts of recruitment, such as resume review, response analysis, or basic verification checks. These tools assist the recruitment team and do not replace human judgment; final hiring decisions are made by people.