Decision Scientist

At Instructure , we believe in the power of people to grow and succeed throughout their lives. Our goal is to amplify that power by creating intuitive products that simplify learning and personal development, facilitate meaningful relationships, and inspire people to go further in their education and careers. We do this by giving smart, creative, passionate people opportunities to create awesome. And that's where you come in: The Decision Scientist at Instructure will contribute to how data informs strategic decisions across the organization. This is a foundational role within a growing decision science capability, offering the opportunity to apply analytical rigor to meaningful business problems in an EdTech environment. Impact of the Role As a Decision Scientist, you will support data-driven decision-making across Instructure by delivering high-quality analyses and partnering with cross-functional teams. In this role, you will: Support business impact through data-driven insights. Conduct analyses that uncover opportunities to improve product adoption, customer engagement, and revenue growth using rigorous analytical methods. Execute experimentation and causal analysis. Support the design and execution of A/B tests and causal inference studies to evaluate the impact of new product features, pricing strategies, and go-to-market initiatives. Contribute to product and business strategy. Partner with product managers, engineers, and marketing teams to translate business questions into structured analytical frameworks and deliver clear, actionable findings. Deliver analytical solutions end-to-end. Own the lifecycle of analytical projects — from scoping problems and building models to presenting insights and tracking outcomes. Apply AI-first thinking. Leverage AI tooling (e.g., Claude, ChatGPT, Glean) to accelerate analysis, improve throughput, and elevate the quality of deliverables. Communicate insights clearly. Translate analytical findings into recommendations that both technical and non-technical stakeholders can understand and act on. What You Will Need Master's degree in Statistics, Computer Science, Economics, Applied Mathematics, Operations Research, or a related quantitative field (PhD is a plus). 2–4 years of experience in data science, analytics, or a related discipline with demonstrated ability to deliver actionable insights. Strong understanding of statistical modeling, machine learning fundamentals, and experimental design (A/B testing). Familiarity with AI tooling (Claude, ChatGPT, Glean) to improve productivity. Strong proficiency in SQL for data extraction and manipulation. Proficiency in Python or R for data analysis, modeling, and visualization. Proficiency in a Business intelligence tool (Tableau, PowerBI... etc.) Experience working with modern data platforms (e.g., Snowflake, Databricks, Fivetran). Strong communication and storytelling skills with the ability to present complex analyses clearly. Experience in SaaS, product analy