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Instructure is seeking a Director of Decision Science to build and lead the decision science function. You will own the people, roadmap, and standards for the team that transforms Instructure's data into actionable business decisions.
In this people-leadership role, you will hire, coach, and develop a team of decision scientists while maintaining hands-on involvement in analytical work. You'll set the bar for analytical rigor across the company and ensure that leaders act on data-driven insights.
Key responsibilities include:
- Building and leading the decision science team through hiring, onboarding, coaching, and career development
- Setting the function's strategy, roadmap, and success metrics
- Partnering with product, engineering, marketing, finance, and executive leadership to translate business questions into analytical problems
- Directing development of predictive, prescriptive, and causal models for product decisions, customer retention, pricing, and operating efficiency
- Elevating how insights reach decision-makers through dashboards, metric definitions, and executive readouts
- Presenting findings and recommendations to senior leaders with clarity on what is known, unknown, and recommended actions
- Growing data literacy across the organization
- Collaborating with data engineering and platform teams on data, tooling, and infrastructure needs
- Upholding ethical and privacy-conscious data use, including student data governance and regulatory compliance
Instructure is an education technology company focused on creating intuitive products that simplify learning and personal development. The role sits at the intersection of product, engineering, marketing, finance, and executive strategy.
REQUIREMENTS:
- 10+ years of experience in data science, analytics, or decision science, including at least 3 years managing and developing a team
- Track record of analytical work that changed real decisions and produced measurable business results
- Deep expertise in experimental design, causal inference, statistical modeling, and machine learning
- Strong SQL skills and fluency in Python or R
- Experience with modern data platforms (Snowflake, Databricks, Spark, or similar)
- Ability to explain complex analysis to executives in plain language and defend methodology to technical peers
- Proven track record of hiring well, developing people, and building strong team culture
- Comfort setting priorities in fast-moving environments with changing questions and imperfect data
- Master's or PhD in statistics, economics, computer science, operations research, applied mathematics, or related quantitative field (or equivalent practical experience)
NICE TO HAVE:
- Experience in education technology or B2B SaaS
- Familiarity with subscription and product-led growth metrics (retention, expansion, adoption)
- Experience building an analytics or decision science function from early stage
