Data science állások, munkák

• Shape and implement the company’s data science strategy and drive innovation, with a primary focus on Generative AI and Agentic workflows
• Identify opportunities to leverage data for business value and impact
• Take ownership of the full technical stack for development and deployment

FLEXIBILITY- The times of punishments for coming 5 minutes late are gone. We have flexible home office policy as well!...

• Owning a revenue target across data, advanced analytics, and predictive AI
• Leading executive-level client conversations, joining deals early to diagnose the business problem, structure a solution, and build the ROI case that gets the client to sign

• Design and build backend services and APIs supporting data ingestion, transformation, and delivery to frontend and downstream consumers
• Own data storage and pipeline architecture including integration with streaming/event infrastructure

As Data Integrity Specialist, You will lead data integrity activities to protect the completeness, accuracy and availability of quality and manufacturing data. You will work closely with site quality, IT, manufacturing and global quality teams. We value clear thinkers who act with integrity, who...

Ready to fast‑track your career and take on real global challenges? ...

• Geographic information systems, spatial analysis, and map server infrastructure
• Maintain a performance oriented GeoServer and database
• Create new features based on specification
• Actively take part in the system design
• Optimize data flows, build automated data piplines

• Managing day-to-day operations of Databricks data pipelines, including monitoring, troubleshooting, and performance tuning
• Maintaining Delta Lake data layers (bronze / silver / gold), ensuring data availability, consistency, and smooth pipeline execution

• Definition and improvement of metrics reflecting product performance, service quality, and operational efficiency
• Analysis of client behavior and service processes to identify trends, bottlenecks, inefficiencies, and drivers of performance

• Design, develop, and maintain high-quality C++ software components and services.
• Build and integrate scalable APIs, database solutions, and data-processing pipelines.
• Collaborate with data scientists and operations research specialists to bring models into production and industrialize their code.

• Lead annual and periodic User Developed Application (UDA) assessments and certifications, ensuring compliance with bp controls and regulatory requirements
• Partner with participants, application owners and technical teams to identify, assess and remediate control gaps, reducing risk

• Lead implementation of AI, GenAI, ML, automation, and AI-powered applications.
• Translate solution designs and requirements into development plans and working software.
• Drive engineering delivery aligned with the target architecture.

Broaden your horizon (literally) by collaborating with our Talent Acquisition team all over Europe and work within a globally aligned and rapidly growing Global Talent Acquisition function...

• Design and implement algorithms to process and analyze sensor data from sources like LiDAR, images, and satellite imagery
• Create algorithms to transform sensor data into actionable insights, such as reconstructing 3D models, segmenting spatial data, or detecting environmental features

• Discovery & Shaping: Lead stakeholder workshops, translate business needs into MVP scopes, and map out scalable implementation roadmaps.
• End-to-End Architecture: Design and document (C4 diagrams, API contracts) robust cloud architectures covering application, data, and LLM layers.

• End-to-end AI solution ownership from problem definition through prototype validation and production support
• Partnership with product managers and business stakeholders to translate real-world problems into data science and AI initiatives

• Geographic information systems, spatial analysis, and map server infrastructure
• Maintain a performance oriented GeoServer and database
• Create new features based on specification
• Actively take part in the system design
• Optimize data flows, build automated data piplines

• collaborating on the design and development of ML‑based applications and their backend components
• helping to select the most applicable solutions for a given business problem
• writing clean, efficient and well‑documented code
• contributing to our MLOps processes

• Lead the architecture, design, and implementation of enterprise-scale web applications using modern frontend technologies
• Serve as the technical lead for UI development while remaining actively involved in coding, design reviews, and implementation

• Design, build and deploy LLM-powered pipelines and autonomous agents
• Scope and deliver AI solutions in collaboration with stakeholders
• Set best practices around MLOps and production-grade AI
• Mentor junior and mid-level developers
• Contribute to internal knowledge-sharing