Top Data & Analytics Jobs

The ML Research Scientist will lead research on large language model (LLM) safety, focusing on developing innovative techniques for safe, high-quality, and explainable models. Responsibilities include spearheading research, co-authoring papers, collaborating with teams, and delivering scalable algorithms.

The postdoc will support machine learning research for decision support, contributing to AI and turbulent flow simulations. Responsibilities include designing AI algorithms, implementing uncertainty quantification methods, and deploying these methods on high-performance computing systems to enhance simulations.

The Lead Data Architect will design and implement data architecture strategies, collaborate with IT and business teams to define data standards, and create optimized data structures for effective data management. Responsibilities include developing data models, solutions, and documentation while ensuring compliance with architecture strategies.

The Data Science Manager will lead and mentor a team of data scientists, develop and implement data science strategies, manage day-to-day operations, and ensure project delivery. They will conduct data analysis and modeling, communicate insights, and collaborate with various departments to drive business growth through data science initiatives.

This role involves initiating and conducting independent research projects to enhance scientific knowledge and improve patient outcomes. The Research Scientist collaborates with internal and external teams on research design and analysis and manages research funding responsibly.

The Manager of Marketing Technology and Data Operations oversees the marketing technology stack at Berklee College of Music, managing platforms like Salesforce Marketing Cloud, optimizing data capture, and ensuring effective marketing campaign execution. This role involves collaboration with stakeholders to enhance workflows, improve customer engagement, and support data-driven decision-making.

The Senior Analyst, Strategic Analytics for Midscale Brands supports analytical needs through strategic analysis and insights. Responsibilities include tracking success, applying predictive techniques, collaborating with various teams, preparing strategic reviews, and promoting innovative problem-solving approaches within a dynamic environment.