We’re looking for a Data Scientist to join our tech team and help build the future of neuro-contextual advertising at global scale. Who We Are At Seedtag, our mission is to transform advertising by proving that effectiveness and user privacy can truly coexist. As the leading Neuro-Contextual Advertising Company, we combine Artificial Intelligence, Natural Language Processing, Computer Vision, and neuroscience to understand not only what content is about, but how it makes people feel and what they intend to do next. Our proprietary AI, Liz, enables brands to connect with audiences across the open web and Connected TV without cookies or user tracking. Founded in 2014 by two ex-Googlers, Seedtag has grown to 700+ Seedtaggers in 17 countries, backed by €250M in funding, and operates today as a global ad-tech leader. If you enjoy solving complex engineering challenges and building AI-driven systems at scale, you’ll feel right at home here. Your Challenge As Data Scientist, you will: - As a member of our data science team, you will build production-grade AI agent systems that interact with data, execute multi-step workflows, and make autonomous decisions impacting business outcomes. - You will design and implement agent architectures using modern frameworks, working on multi-agent orchestration patterns, agent delegation, and ensuring reliable execution under production constraints. - You will solve context management challenges across conversation history, tool outputs, and file attachments, implementing semantic search and retrieval systems to ensure agents have the right information to answer questions accurately. - You will integrate agents with data infrastructure, connecting them to databases and APIs in real-time, and implement tool integration systems that enable scalable development across teams using protocols like MCP. - You will build evaluation frameworks to measure agent performance in production, taking solutions from concept to deployment, and collaborating closely with cross-functional teams to align your work with business goals. Our Core Values Outcome over Output We measure success by impact and value, not by volume of features or lines of code. Failure Is Allowed, Learning Is a Must Experimentation is key to innovation. We test early, iterate often, and learn fast. We Are All Scouts We take ownership and leave things better than we found them. We Are Data-Driven Data informs our decisions and helps us continuously improve our systems and results. Tech Stack We operate at large scale, supporting up to 120k requests per second, with ML models responding in under 10 milliseconds and processing 20 TB of data daily. Our stack includes: - Languages: Python, Go, TypeScript, Scala - Cloud & Infrastructure: Kubernetes, GCP, AWS - Streaming: Kafka, Kinesis - Data: Datalakes, GCS, Redis, Druid, MongoDB - Architecture: 100+ microservices, DevOps-driven, continuous deployment What You’ll Need to Succeed - You bring 3-5 years of experience building and deploying production ML systems, with hands-on experience developing LLM-based applications or autonomous agents using frameworks like Pydantic AI, OpenAI Agents SDK, LangGraph, or similar, and the ability to adapt as the ecosystem evolves. - You possess strong software engineering skills with proficiency in Python and a track record of deploying services to production, including experience with async programming, API design, and production infrastructure like Docker and Kubernetes. - You have a strong academic background in fields such as Computer Science, Engineering, Statistics, Mathematics, or similar, with a focus on quantitative analysis and problem-solving, plus understanding of retrieval systems, embeddings, or context management patterns. - You have hands-on experience with end-to-end project workflows from design to deployment, understand multi-step agent workflows and tool calling patterns, and can handle the non-deterministic nature of LLM-based systems. - You are proactive, entrepreneurial, and adaptable, comfortable working in a fast-moving environment where best practices are still emerging, and committed to building reliable AI agent systems that drive measurable business outcomes. Why Join Seedtag? - A key moment of growth with real ownership and global impact. - Flexible work model with 100% remote or hybrid options. (Remote contracts available in Spain, Italy, UK, Belgium, Netherlands, France, and Germany.) - Continuous learning through a learning platform and optional language classes. - A supportive, trust-based culture that values well-being. - Team activities, offsites, and opportunities to connect beyond work. Additional Perks - Home office setup budget up to €1,000 - Paid trips to our HQ in Madrid - MacBook Pro M3 Ready to Join the Seedtag Adventure? At Seedtag, we create an environment where everyone can thrive. If you need accommodations during the hiring process, let us know and we’ll ensure a positive experience. Send us your CV and let’s build the future of neuro-contextual advertising together.

• Develop, deploy, and maintain Machine Learning models and systems • Perform data analysis, preparation, and processing for ML workflows • Contribute to ML system design, including data annotation and processing pipelines • Follow security guidelines and identify potential risks in solutions • Collaborate on design reviews to ensure robustness and reusability • Support engineering delivery processes and resolve issues • Ensure correct deployment and stable operation of features • Create and maintain documentation for ML models and processes • Monitor deployed solutions and ensure performance standards are met • Promote reuse of internal technologies and solutions

Role Description Bist du auf der Suche nach einem Job, mit dem du etwas Geld verdienen kannst, während du dein Lieblingsfach unterrichtest? Bei Nachhilfeunterricht suchen wir begeisterte und enthusiastische private Lehrkräfte. Wir haben eine große Zahl von Schülern, die täglich Nachhilfelehrer für ihre Schul- oder Universitätsfächer anfordern. - Du wirst mit den Studenten den Tarif und den Zeitplan vereinbaren. - Du wirst ein Fach deiner Wahl unterrichten und deine eigene Methodik entwickeln (wie du den Unterricht gestalten wirst). Qualifications - Kommunikationsfähigkeit und gute Kenntnisse in dem Fach, das du unterrichten wirst. Benefits - Flexible Arbeitszeiten, bestimme den Zeitplan deines Nebenjobs je nach deiner Verfügbarkeit. - Home Office: Möglichkeit Remote/von zu Hause aus zu arbeiten. - Du bestimmst dein eigenes Nebenjob-Gehalt (15€- 30€).

• Own the full modeling cycle — from exploring raw data to preparing production-ready specs • Use metrics like AUC, KS, bad rate, and stability index to validate model quality • Track how models perform after launch and know when it’s time to retrain or adapt • Evaluate value through NPV, backtesting, and real-world portfolio performance • Translate insights into decisions — you’ll help evolve our credit strategy, not just build models • Contribute ideas that change how we approve, price, and manage credit — our internal tools are flexible and data-driven • Work closely with product and data to align every model with real business goals • Step in beyond your scope when needed — we value ownership over rigid roles • Every task is evaluated through the lens of business value — no "models for the drawer" here