FlowRx- Senior Data Scientist

Description We are looking for a creative, impact-oriented Senior Data Scientist to join our growing team. We are at an era of rapid scaling as FlowRx deploys advanced AI solutions to eliminate critical pharmacy errors and protect operating margins. This role is ideal for a strong data scientist who combines deep scientific thinking and an analytical approach to data with a product mindset, and enjoys taking models all the way from research and experimentation into production. You will work on complex, high-impact problems across ML and data-driven product development, and play a key role in shaping both our modeling direction and our data science standards and deliverables. Responsibilities Lead E2E data science initiatives, from problem definition and research through data exploration, modeling, evaluation, deployment, and ongoing monitoring Design, implement, and deliver robust, scalable machine learning solutions that can operate reliably in production environments Develop and improve models across a range of data science domains, with a strong emphasis on data extraction, retrieval, and LLM-based agentic systems, alongside NLP and other applied machine learning challenges Translate ambiguous business and product needs into clear analytical approaches, data pipelines, experiments, and production-ready models Define success metrics, evaluation frameworks, and monitoring approaches to ensure model quality, performance, and business impact over time Drive best practices in experimentation, code quality, peer review, reproducibility, and scientific rigor across the team Identify opportunities to improve existing methodologies, tools, and processes to increase efficiency, accuracy, and scalability Requirements Requirements 5+ years of hands-on experience in Data Science At least 3 years of leading data science projects through production, adoption, and monitoring. Master’s degree in Computer Science/ Mathematics/ Statistics/ Engineering - MUST Strong track record of turning research or early ideas into production-grade machine learning systems Hands-on experience building with Python Experience building and evaluating LLM-based AI systems — context engineering, RAG approaches, and designing evaluation harnesses for generative outputs Experience working with large-scale datasets and production environments, including collaboration with engineering teams on deployment and monitoring Experience working with AI coding agents (e.g. Claude Code) as a core part of the daily workflow — research, scripting, data exploration, and pipeline development High ownership, strong problem-solving skills, and the ability to operate effectively in a dynamic, fast-moving environment Nice to Have Experience with cloud machine learning platforms such as AWS SageMaker, Vertex AI, or similar environments Experience with MLOps tools and practices, including model versioning, experiment tracking, CI/CD for ML, and production monitoring Experience with LLM-based workflows, retrieval systems, ranking, recommendation, or other advanced applied AI use cases Experience working in a product company and building customer-facing ML capabilities Background in fast-paced startup environments Why Join Join a team at an exciting stage where you can influence both the product and the data science direction Work on meaningful, high-impact machine learning problems that move from research into real customer value