Top Data Science Jobs in Germany

Lead the inventory product domain within Zalando’s Fulfillment Core, defining vision, strategy, roadmap, KPIs, and customer-focused product outcomes. Build and deploy technical platform products at scale, use data and AI technologies for discovery, experimentation, prototyping, and decision-making, and navigate complex cross-functional trade-offs. Partner with Design, Engineering, and Data Science, maximize commercial value, and mentor other product managers.

Leads EBV-wide commercial excellence strategy across purchasing and sales, focusing on pricing, margin optimization, profitability, customer segmentation, and commercial productivity. Establishes KPI and margin-monitoring frameworks, identifies leakage and improvement opportunities, develops strategic business cases, and translates analytics into actionable initiatives. Partners with business intelligence, digital innovation, sales, procurement, marketing, and operations leaders while advising senior management and leading cross-functional projects.

Develop GreyNoise’s cybersecurity channel business across Europe by recruiting and activating partners, building joint business plans, enabling partner teams, generating qualified pipeline, and co-selling enterprise and government opportunities. The role manages partner relationships, channel strategy, revenue targets, forecasting, commercial negotiations, partner reviews, technical enablement, demand generation, and cybersecurity event representation.

Leads the Data Tribe, establishing data governance and management standards, ensuring engineering compliance, and identifying data-driven business opportunities. Oversees data infrastructure and analytics, advises teams on data-driven practices, mentors Team Leads, manages stakeholders and projects, and serves as Data Protection Coordinator for Engineering.

Own the Mapping & Content product domain end to end, including strategy, prioritization, economics, and outcomes. Lead efforts to match hotel rooms and content across suppliers, languages, and formats with high accuracy and coverage. Partner closely with engineering and data science teams on entity resolution, search, matching, catalog, identity, recommendation, and content-quality problems. Identify high-value failures, make trade-offs between precision and coverage, and help build Nuitee’s product organization in a fast-moving environment.

Leads flavor analysis, analytical method development, and complex data interpretation for pet food innovation and quality. Partners with data scientists, academic researchers, suppliers, and cross-functional teams to translate aroma and taste compound analyses into product, raw material, and business insights. Manages strategic analytical capabilities and complex technical projects independently.

Leads enterprise AI and automation strategy, governance, platform scaling, reusable AI services, production deployment, and high-value use-case prioritization. Advises senior leaders, aligns business and technology stakeholders, establishes responsible AI frameworks, and develops operating models that drive adoption, productivity, and business value. The role also monitors emerging technologies and translates complex technical developments into strategic recommendations.

Leads strategic R&D engagements from presales through delivery, translating scientific and business challenges into AI architectures, product backlogs, MVPs, simulations, integrations, data pipelines, and production solutions. Builds trusted relationships with R&D executives, scientists, engineers, and technical teams; assesses data, compute, feasibility, value, staffing, and delivery plans. Develops reusable architectures and playbooks, oversees technical workstreams, evaluates emerging AI capabilities, and provides feedback to shape Microsoft Discovery products and scalable industry solutions.

Develop and deploy scalable, production-grade machine learning and AI solutions for financial research. Build LLM- and NLP-based applications, collaborate with senior engineers, and contribute to reliable AI-driven products. Responsibilities require Python, software engineering, deep learning, databases, Docker, and at least one major deep learning framework. Preferred experience includes RAG pipelines, vector databases, LLM fine-tuning, cloud platforms, and Kaggle competitions.

Own end-to-end pricing and forecasting models for holiday homes, including demand, price sensitivity, and conversion prediction. Develop dynamic pricing strategies, run production experiments, monitor model performance, and iterate models. Translate business questions into testable approaches, make technical decisions, and collaborate with analysts and engineers on datasets and features. Apply machine learning, statistics, and AI tools to improve occupancy and host earnings.

Develop, validate, and deploy computer vision and machine learning algorithms for clinical decision support using imaging and sensor data. Own projects from messy data and modeling through rigorous evaluation and production integration. Collaborate with hardware, software, medical, and clinical research teams, apply classical and deep learning methods, support regulatory readiness, deliver production-quality Python code, and mentor colleagues.

Chief of Staff to the VP of Data Science & Analytics, responsible for strategic planning, reporting cycles, operational governance, leadership coordination, cross-functional initiatives, events, and team engagement. The role drives execution of data strategies, supports AI workflow integration, facilitates decision-making, manages recurring programs, and improves operating processes across a 300-plus-person function.

Lead the data intelligence dimension of Agileday’s AI product by building AI-ready data foundations, predictive and recommendation capabilities, learning systems, feedback loops, and production data pipelines. Partner with founders and product teams to identify commercially valuable opportunities, shape architecture and quality standards, and move solutions from experimentation into reliable customer-facing products.

Lead data science and credit risk strategy across Southeast Asia. Build and oversee production machine learning models for underwriting, fraud detection, risk segmentation, and real-time decisioning. Establish credit policies, monitor portfolio performance, lead stress testing, and support responsible market expansion. Build and mentor data science and risk teams while partnering with engineering, product, finance, and executives to improve approvals, defaults, time-to-decision, and unit economics.

Leads complex enterprise accounts across the full technical sales lifecycle, delivering demos, pitches, prototypes, and cloud proofs of concept. Partners with C-level stakeholders, mentors Solutions Architects, develops regional best practices, and builds Databricks’ technical presence in the DACH market through workshops, collateral, meetups, and conferences. Requires deep data engineering or data science expertise, hands-on Python and SQL coding, fluent German and English, AI-assisted development experience, and strong public cloud knowledge.

Develop and demonstrate Physical AI solutions on NVIDIA and hyperscaler platforms. Advise customers and partners, optimize GPU-accelerated training and inference pipelines, conduct proof-of-concepts, and collaborate with Engineering, Product, Sales, and Marketing teams. Build technical relationships, gather customer feedback, support enterprise architecture integration, and evangelize accelerated computing and generative AI to developers, researchers, executives, and technical leaders.

Leads and grows a distributed EU-based AI and Machine Learning team, managing Data Scientists and Machine Learning Engineers. Responsibilities include line management, coaching, performance reviews, team culture, delivery processes, engineering quality, CI/CD, cloud automation, monitoring, architecture discussions, process improvement, and cross-regional stakeholder collaboration. The role partners with AI leadership on technical, organizational, and HR matters.

Lead technical discovery, solution design, demonstrations, and proof-of-concept support for Anaconda’s AI and data science platform across EMEA. Partner with account executives on complex deals, create reusable technical content, represent customer needs to product and engineering, and coordinate with cross-functional teams through implementation handoff. Manage multiple opportunities independently while improving technical win rates, deal expansion, sales velocity, and regional pipeline development.

Advise C-level life sciences and healthcare executives on AI and data strategies, lead large-scale digital transformations, develop client relationships, generate consulting business, oversee major client portfolios, and guide cross-functional teams in designing, implementing, and scaling AI and data solutions.

Assess credit applications using multiple data sources and a tech platform to make fast, fair decisions. Grow decisioning autonomy, support peers on complex cases, and collaborate with analytics to optimise lending models and processes.

Lead GTM strategy and product positioning for key products, create messaging and content, run campaigns and launches, analyze market and competitive trends, and collaborate cross-functionally to drive adoption, pipeline growth, and customer engagement.

As a Software Engineering Consultant at Netlight, you'll work on digital projects, shaping software products and solutions while defining your career path and collaborating with a dynamic team.

The Account Executive will leverage technical expertise in enterprise SaaS sales to drive revenue growth, build partnerships, and represent Neural Concept's technology in engineering sectors.

The AI Product Manager will drive the development of AI-powered applications, collaborating with engineering and design teams, conducting market research, and optimizing AI models to align with user needs.

Manage strategic partnerships and maritime defence programmes, driving complex projects from engagement to delivery while collaborating with government and industry stakeholders.