About Interval
Interval helps enterprises turn messy, underused data into governed, high-confidence intelligence—without handing control to a black box. We bring compute to your data with a private data lakehouse, verifiable audit trails, and U-AI , our contextual AI framework for secure AI workflows.
Our platform is built around three outcomes: - Control: Keep ownership of your data and how models use it. - Verify: Audit what happened, why it happened, and where results came from. - Monetize: Create new revenue opportunities through private, permissioned data exchange.
Role Overview As a Data Scientist at Interval, you will design, build, and deploy advanced analytics and machine learning models that drive value for enterprise clients across diverse industries, all while upholding the company’s privacy-first ethos and commitment to data sovereignty. In this role, you will collaborate closely with data engineers to create robust, trustworthy data pipelines and ensure reliable model deployment, while also researching, evaluating, and implementing techniques to rigorously quantify, monitor, and improve the performance and explainability of AI solutions. You’ll work at the intersection of cutting-edge technology and real-world business needs—extracting insights from complex datasets, supporting regulatory compliance, and helping organizations realize the value of their data without compromising security or transparency.
Key Responsibilities - Design, build, and deploy AI/ML models for diverse business applications, emphasizing privacy and compliance. - Partner with data engineers and AI/ML engineers to develop robust, trustworthy data pipelines and ensure reliable model deployment. - Implement privacy-first analytics techniques, supporting data sovereignty and regulatory compliance. - Scale analyses of large, complex datasets to extract meaningful insights and identify actionable opportunities. - Collaborate with stakeholders to scope projects and communicate key findings. - Monitor, evaluate, and improve the performance and explainability of AI solutions. - Develop and maintain clear documentation, experiment logs, and analytic artifacts.
Qualifications - Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. - Demonstrated experience with machine learning, statistical modeling, and analytics. - Proficiency in Python (or similar language), SQL, and relevant ML/data science libraries. - Strong knowledge of privacy-preserving techniques (federated learning, differential privacy) or interest in privacy-first AI/ML development. - Knowledge of data engineering/big data tools (e.g., Spark, Airflow, Kafka) is beneficial. - Experience working on cloud, hybrid, and/or on-premise infrastructure. - Familiarity with regulatory environments (GDPR, CCPA) and data sovereignty issues is a plus. - Excellent communication and problem-solving skills; curiosity and adaptability.
Why Interval? - Impact: Shape a platform that enables enterprises to control, secure, and monetize their most valuable asset—data. - Innovation: Work at the intersection of AI, privacy, and data infrastructure. - Growth: Collaborate with a dynamic team revolutionizing data use across multiple industries.