Über
A g rowing AI organization is seeking a highly skilled Lead Data Scientist with deep expertise in modern AI technologies. The ideal candidate will apply advanced knowledge in machine learning, natural language processing, and artificial intelligence to design, develop, and deploy models that accelerate innovation and support strategic decision-making. This role will focus on delivering measurable impact through outcome-driven AI initiatives, leading data science efforts from concept through deployment, and driving automation value streams.
Key Responsibilities
Part
ner with product leadership to manage the full AI development lifecycle, including requirements gathering, data sourcing, model development, proof-of-concept builds, risk reviews, and production deployment across on-premises and cloud environments. Demonstrate strong ownership and self-discipline in managing project activities, maintaining clear communication with leadership, and proactively escalating risks or resource needs. Apply automation techniques to streamline manual processes, improve accuracy and productivity, and build reusable, scalable self-service tools and assets. Stay current on emerging AI, machine learning, and cloud technologies, integrating new capabilities into workflows and products. Lead data science initiatives from concept through deployment, ensuring measurable business impact. Required Qualifications
Ph D or Master's degree in Statistics, Economics, Data Science, or related field. 3-5 years of enterprise data science experience. Hands-on experience with cloud-based machine learning platforms (AWS preferred; Azure or GCP acceptable). Proficiency in Python (preferred) or R, Spark, and other modern data science tools. Working knowledge of Large Language Models (LLMs) such as Llama, Claude, Titan. Experience with LangChain-style frameworks, vector databases, embeddings, and pro mpt engineering. Preferred Qualifications
Han ds-on experience with LLM fine-tuning. Understanding of advanced Retrieval-Augmented Generation (RAG) techniques (MMR, multi-vector retrieval, RAG-fusion, HYDE, self-RAG, retrieval evaluation). Knowledge of agent-based AI workflows including task orchestration, multi-agent collaboration, and workflow automation. Experience with advanced cloud AI/ML services such as foundation model APIs, cloud-native AI hosting, or document intelligence tools. Willingness to step beyond traditional modeling tasks to address broader technical or business challenges. Certification
None required; certifications in cloud AI/ML platforms or data science frameworks are a plus.
Sprachkenntnisse
- English
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