Top Data Science Jobs in Germany

Develop and optimize chemical, fuel, and refining processes with economic and sustainability focus. Model biorefinery processes, assess new installations and retrofits, support technology scale-up/scale-down, and collaborate with teams and partners across project phases.

Lead end-to-end delivery of multiple software projects by creating and managing plans, running agile ceremonies, tracking KPIs, coordinating distributed teams and stakeholders, mitigating risks, and ensuring on-time delivery using project management tools (Linear).

Assess small-business credit applications using multiple data sources and a tech platform to make fast, fair, and accurate decisions. Provide autonomous decisioning that grows with experience, support colleagues on complex cases, and work with analytics to optimise lending approaches. Interpret financial statements, evaluate risk and revenue drivers, and apply practical, data-driven solutions in a fast-paced environment.

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.

Assess SME credit applications using company data and tech platform, make autonomous data-driven lending decisions, support complex cases, work with analytics to optimise credit strategy, and continuously improve 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.

Drive development and deployment of AI solutions, translating business needs into product requirements, managing backlogs, and coordinating cross-functional teams.

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 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.

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.

Kittl seeks innovative individuals for engineering and product roles. Applicants should show passion for design, ownership, and collaboration. Areas include frontend, backend, full stack, data, and product management.

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

Responsible for managing market communication processes, overseeing data exchange between market partners, and addressing process issues. Optimize system errors and act as a liaison via email and phone.

Lead end-to-end ML product roadmaps and initiatives (e.g., Attachment Matcher, Transaction Categorizer). Collaborate with data scientists, engineers, and stakeholders to define, deliver, and monitor ML solutions that drive measurable business value for SMEs across Qonto's platform.

The Senior Scientist, Data Science will lead data-driven and AI-based projects, developing ML models and MLOps workflows in the life sciences field.

Lead the end-to-end search experience: improve relevance, discovery, ranking, and UX across platforms. Collaborate with data science/ML to define metrics and experiments, prioritize a roadmap, and optimize search infrastructure, autocomplete, filters, and zero-results handling for complex health-related journeys.

As a Customer Impact Engineer, you manage customer integration projects, optimize production processes, and create scalable AI solutions for enterprise clients.

Lead and grow the Data Science team owning the real-time bidding algorithm, combine hands-on modeling with people leadership, architect and deploy large-scale ML systems, run experiments and A/B tests, and align model work with product and infrastructure priorities to drive ad monetization and business outcomes.

Lead a squad of 4–7 data scientists and ML engineers to define technical strategy and deliver data science solutions for dynamic promotions. Translate business problems into technical work, oversee model lifecycle, apply classical ML and causal methods, run A/B testing, and collaborate with product and stakeholders to optimize promotional efficiency and operational performance.

As a Data Analytics Intern, you will analyze data sets for trends, support strategic questions, improve credit risk models, and build dashboards.

PhD students will research wearable intelligence, multimodal data fusion, and on-device/edge AI to build privacy-preserving, personalized systems and knowledge-grounded digital avatars, collaborating with academia and industry and contributing to prototypes and publications.

Conduct PhD research on wearable intelligence, multimodal data fusion, and edge AI. Develop on-device processing, compact micro-LLMs, and privacy-preserving personalization systems; collaborate with academia and industry to build prototypes, publish findings, and support education-focused AI applications.

Lead a team of 4–6 Decision and Data Scientists to own and scale marketing measurement: attribution, MMM, LTV modelling, experimentation, and long-term effect measurement. Build repeatable, self-service analytics using AI and modern tooling, act as hands-on senior sparring partner for complex projects, and partner cross-functionally to turn models into budget and marketing decisions.

Provide data-driven insights and decision support for customers using data analysis, model configuration, tuning, simulations, and visualization. Support pricing and cognitive solutions, present findings, define success metrics, adhere to ITIL support processes, and travel to customer sites (~10%).

Lead and mature the analytics and data science function: hire, coach and develop data professionals; integrate AI into workflows; manage the data roadmap and deliver measurable business impact; collaborate with engineering and business teams; prioritize high-impact marketplace optimization, modeling, and experimentation initiatives.