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- Aufgaben: Join us as a Data Scientist focusing on data quality and AI-driven automation.
- Arbeitgeber: Orderfox is revolutionizing industrial intelligence with cutting-edge AI solutions.
- Mitarbeitervorteile: Enjoy a tech-first culture, career growth opportunities, and work with the latest AI technologies.
- Warum dieser Job: Be at the forefront of AI innovation and shape the future of industry intelligence.
- Gewünschte Qualifikationen: Proficiency in Python, SQL, and experience with LLMs and big data processing required.
- Andere Informationen: This role is EU-based; no VISA support available.
Das voraussichtliche Gehalt liegt zwischen 54000 - 84000 € pro Jahr.
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Data Scientist – Data Quality and Completeness CHF90-110k, Zürich District
Client:
Partfox
Location:
Job Category:
Other
Job Reference:
338926321bea
Job Views:
4
Posted:
06.03.2025
Expiry Date:
20.04.2025
Job Description:
About Orderfox
Orderfox is redefining AI-driven industrial intelligence with cutting-edge solutions for data-driven decision-making and smart procurement automation. Our mission is to empower businesses with next-generation AI tools that enhance operational efficiency, uncover market insights, and drive competitive advantage.
Our Products
- Gieni AI – An advanced AI-powered market intelligence engine that analyzes data from over 380 million websites worldwide, providing businesses with real-time insights, deep industry analytics, and predictive intelligence to stay ahead of the competition.
- Partfox – An AI-powered, commission-free platform that connects buyers with manufacturers based on precise CNC machine capabilities . Buyers can upload part specifications (STEP, PDF) and receive instant matches with suitable manufacturers. The platform ensures transparent, efficient procurement by enabling direct communication without intermediaries.
Tasks
– We can only accept applications from within the EU – no VISA support –
We are looking for a Data Scientist specializing in data quality, completeness, and AI-driven automation , with a strong focus on LLM-powered retrieval and process orchestration.
This role is not about traditional machine learning model training—our focus is on agentic AI workflows , efficient data processing, and scalable automation using LLMs via inference APIs (OpenAI, Bedrock, AI Foundry, etc.). You will work with distributed computing, data lakes, vector search, and retrieval-augmented generation (RAG) techniques to optimize knowledge access for AI-driven applications.
Core Focus Areas (Top Priorities)
- Agentic Prompt Engineering – Designing dynamic LLM prompts, chains, and automation workflows.
- Distributed Computing & Process Orchestration – Managing large-scale workflows with automation and fault tolerance.
- Data Lake Access & Processing – Efficiently handling big data retrieval, querying, and optimization.
- Vector & Semantic Search – Building high-performance search and retrieval systems for LLM-powered AI.
- Advanced / Agentic RAG – Implementing next-generation knowledge retrieval architectures.
Additional Responsibilities
- Ensure data quality & completeness across large-scale structured and unstructured datasets.
- Automate data validation, cleansing, and transformation for LLM & AI pipelines.
- Develop scalable vector databases & search solutions to improve retrieval efficiency.
- Work with graph databases for knowledge representation and structured reasoning.
- Optimize RAG-based AI pipelines for fast, contextually relevant information retrieval.
- Collaborate with engineers & AI researchers to refine data access and orchestration.
- Version control & automation using Git and CI/CD best practices.
- Stay updated on latest AI trends, LLM advancements, and data infrastructure.
Requirements
Required Skills & Experience
- Programming: Python, SQL, R.
- Agentic Prompt Engineering: Langflow, AgentOps, LlamaIndex, AutoGPT frameworks.
- Process Orchestration & Distributed Computing: Airflow, Kestra, AWS Batch, Databricks.
- Data Lake Access & Processing: Presto, AWS Athena for large-scale data retrieval.
- Big Data & Storage: Spark, Hadoop for processing large datasets.
- Cloud Platforms: AWS, GCP, Azure for AI-powered workloads.
- Data Quality & Governance: Ensuring high data integrity & compliance.
- Version Control & Collaboration: Git, CI/CD pipelines for AI workflow management.
- Ethics & AI Governance: Understanding of data privacy and ethical AI applications.
Nice to Have (Bonus Skills)
- Graph Databases (Neo4j, ArangoDB) for AI knowledge graphs.
- MLOps & LLMOps (Docker, Kubernetes) for scalable AI deployments.
- Enterprise AI Data Pipelines – Experience building production-ready AI retrieval systems.
- Be at the forefront of AI innovation – Work with LLMs, agentic AI, vector search, and advanced RAG in a high-impact environment.
- Shape the future of AI-driven industry intelligence – Develop solutions that redefine market research, procurement, and supply chain automation.
- Global impact – Our products power businesses across industries, enabling smarter decision-making and efficiency at scale.
- Tech-first culture – Work with the latest in LLM orchestration, distributed computing, and AI-powered retrieval, collaborating with top engineers and data scientists.
- Career growth and learning – Join a team that values continuous learning, innovation, and professional development.
We Look Forward to Your Application
If you are passionate about AI-driven data quality, retrieval, and process automation, we would love to hear from you. Join us in shaping the future of industrial intelligence and apply today!
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Data Scientist - Data Quality and Completeness CHF90-110k Arbeitgeber: TN Switzerland
Kontaktperson:
TN Switzerland HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Data Scientist - Data Quality and Completeness CHF90-110k
✨Tip Number 1
Familiarize yourself with the specific tools and frameworks mentioned in the job description, such as Langflow, AgentOps, and AWS Batch. Having hands-on experience or projects showcasing your skills with these technologies can set you apart.
✨Tip Number 2
Engage with the AI community by participating in forums or attending meetups focused on LLMs and data quality. Networking with professionals in the field can provide insights and potentially lead to referrals.
✨Tip Number 3
Showcase your understanding of data governance and ethics in AI during interviews. Being able to discuss how you ensure data integrity and compliance will demonstrate your alignment with the company's values.
✨Tip Number 4
Prepare to discuss real-world applications of agentic AI workflows and how you've implemented them in past projects. This practical knowledge will highlight your ability to contribute effectively to their mission.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Data Scientist - Data Quality and Completeness CHF90-110k
Tipps für deine Bewerbung 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Data Scientist position. Familiarize yourself with concepts like agentic AI workflows, data lakes, and LLM-powered retrieval.
Tailor Your CV: Customize your CV to highlight relevant experience in data quality, completeness, and automation. Emphasize your skills in Python, SQL, and any frameworks related to agentic prompt engineering or process orchestration.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI-driven solutions and your understanding of the company's mission. Mention specific projects or experiences that align with their focus on data quality and scalable automation.
Highlight Relevant Projects: If you have worked on projects involving big data processing, vector search, or AI pipelines, be sure to include these in your application. Provide details on your role and the impact of your contributions.
Wie du dich auf ein Vorstellungsgespräch bei TN Switzerland vorbereitest
✨Understand the Role's Focus
Make sure you have a clear understanding of the specific focus areas for the Data Scientist position, such as agentic prompt engineering and distributed computing. Be prepared to discuss how your experience aligns with these priorities.
✨Showcase Your Technical Skills
Highlight your proficiency in programming languages like Python, SQL, and R, as well as your experience with tools like Airflow and AWS. Prepare examples of past projects where you utilized these skills effectively.
✨Discuss Data Quality and Governance
Since the role emphasizes data quality and completeness, be ready to talk about your experience ensuring high data integrity and compliance. Share specific strategies or frameworks you've used in previous roles.
✨Stay Updated on AI Trends
Demonstrate your knowledge of the latest trends in AI, particularly regarding LLM advancements and ethical AI applications. This shows your passion for the field and your commitment to continuous learning.
