• Build and ship classical ML and GenAI pipelines that surface, rank, and explain candidate billing error, audit, and fraud concepts across large-scale healthcare claims data • Advance state-of-the-art research in anomaly detection, information retrieval, and weak supervision, turning research into robust production systems • Accelerate concept generation and concept validation with SMEs by designing human-in-the-loop workflows that enable high-throughput review with strong precision, recall, and traceability • Own end-to-end delivery from problem framing and data strategy to model development, evaluation, deployment, and monitoring, with a focus on reliability and customer outcomes • Partner cross-functionally with Product, Data Engineering, Operations, SMEs, and business leaders to prioritize work, unblock execution, and unlock material financial value • Help scale the team and platform as Machinify grows aggressively toward resale and IPO readiness

• Manage a team of data scientists • Direct the evaluation of trends in project demand • Cultivate and manage major long-term vendor partnerships • Lead the development of relevant insights • Collaborate with analytics teams across Kohl’s • Deploy analytics and/or product management best practices • Create clear connections to the goals of the department • Participate in industry and company-wide analytics forums

• As a working student (m/f/d) in Data Science, you will gain exciting insights into the world of data analysis and machine learning. • You will support us with administrative and organizational tasks and have the opportunity to take on responsibility. • You will actively support Data Science projects and apply various methods from different machine learning approaches. • You will help preprocess and analyze data, create detailed visualizations, and write reports and presentations that communicate valuable insights. • You will contribute new ideas and develop innovative data-driven approaches. • In our agile team, you will work closely with stakeholders to jointly find and implement optimal solutions. • You will also take on your own small projects, which can serve as the basis for your thesis.

• Collaborate with scientists, engineers, and technical product owners to create technical solutions • Deliver production solutions for data extraction, classification, routing, search, and decision-making using foundation models • Manipulate and analyze data programmatically, derive statistically sound insights, and communicate findings that address technical and business considerations • Engineer and evaluate foundation model prompts systematically across domain datasets • Design comprehensive evaluation frameworks using precision, recall, F-1 scores, accuracy, and operational metrics • Own documentation and mentor junior team members through systematic problem-solving approaches • Decompose complex problems into measurable components, optimize across multiple dimensions, and articulate trade-offs