Senior Data Scientist

Company Description Intelligible is building an infrastructure layer that transforms enterprise data into composable reasoning components, enabling AI systems to understand and reuse organizational knowledge. By making these components persistent, auditable, and reusable, Intelligible helps enterprises move beyond generic AI that starts from scratch on every query. The platform is designed to deliver AI that compounds in capability over time, improving accuracy and reliability with continued use. Role Description This is a full-time, remote role for a Senior Data Scientist. The Senior Data Scientist will design, develop, and deploy data-driven models and analytical solutions that power Intelligible AI’s reasoning infrastructure. The role involves close collaboration with engineering and product teams to translate business and research questions into measurable outcomes, as well as creating clear documentation and visualizations to communicate insights to technical and non-technical stakeholders. Qualifications Strong proficiency in core Data Science, including model development, feature engineering, and experimentation. Solid foundation in Statistics, including hypothesis testing, inference, and experimental design. Experience in Data Analytics and Data Analysis for problem framing, exploratory analysis, and performance measurement. Ability to create clear, compelling Data Visualization outputs to communicate complex findings to diverse audiences. Advanced skills in Python or a similar programming language, with experience using common data science libraries (e.g., pandas, NumPy, scikit-learn, PyTorch, or TensorFlow). Hands-on experience building and deploying models in production environments, preferably in cloud-based or distributed systems. Background in working with large or complex datasets, including experience with SQL and modern data platforms or warehouses. Excellent communication skills and the ability to collaborate effectively in a remote, cross-functional team. Bachelor’s or PhD in a quantitative field (such as Computer Science, Statistics, Mathematics, Engineering, or related discipline); an advanced degree is a plus. Experience with AI, ML infrastructure, or enterprise data products is highly beneficial; familiarity with ML Ops, evaluation frameworks, or AI safety and reliability is a plus.