Data Scientist

Summary

Interval is a company that helps enterprises turn messy, underused data into governed, high-confidence intelligence. As a Data Scientist, you will design, build, and deploy advanced analytics and machine learning models while collaborating with data engineers to ensure reliable model deployment and support regulatory compliance.

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

Skills

• 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
• Experience working on cloud, hybrid, and/or on-premise infrastructure
• Excellent communication and problem-solving skills; curiosity and adaptability
• Knowledge of data engineering/big data tools (e.g., Spark, Airflow, Kafka) is beneficial
• Familiarity with regulatory environments (GDPR, CCPA) and data sovereignty issues is a plus

Qualifications

Must Haves

• 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
• Experience working on cloud, hybrid, and/or on-premise infrastructure
• Excellent communication and problem-solving skills; curiosity and adaptability

Nice to Haves

• Knowledge of data engineering/big data tools (e.g., Spark, Airflow, Kafka) is beneficial
• Familiarity with regulatory environments (GDPR, CCPA) and data sovereignty issues is a plus