Director of Decision Science

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.

The role.

We're hiring a Director of Decision Science to build and lead the team that turns Instructure's data into better decisions. You'll own the decision science function: the people, the roadmap, and the standards. Your team will run experiments, build causal and predictive models, and answer the questions that shape our product, pricing, go-to-market, and operating plans.

This is a people-leadership role. You'll hire, coach, and grow a team of decision scientists, and you'll set the bar for analytical rigor across the company. You'll still be close enough to the work to review a model, challenge a test design, or dig into a dataset yourself. But your main job is making your team's work count, and making sure leaders act on it.

You'll sit at the table with product, engineering, marketing, finance, and the executive team. When a decision is expensive, ambiguous, or high-stakes, you're the person who tells us what the data supports and what it doesn't.

What you'll do.

• Build and lead the decision science team. Hire, onboard, coach, and develop a group of scientists and analysts, and own their career growth.

• Set the function's strategy and roadmap. Decide which problems the team takes on, which it declines, and how success gets measured.

• Partner with product, engineering, marketing, finance, and executive leadership to turn fuzzy business questions into clear analytical problems, then deliver answers people can act on.

• Direct the development of predictive, prescriptive, and causal models that inform product decisions, customer retention, pricing, and operating efficiency.

• Raise the bar on how insights reach decision-makers, from dashboards and metric definitions to written recommendations and executive readouts.

• Present findings and recommendations to senior leaders. Say clearly what we know, what we don't, and what you'd do about it.

• Grow data literacy across Instructure so teams ask sharper questions and read results correctly on their own.

• Work with data engineering and platform teams to make sure the team has the data, tooling, and infrastructure it needs.

• Hold the line on ethical, privacy-conscious data use, including student data. Follow applicable regulations and our own standards, and make sure your team does too.

What you'll bring.

• At least 10 or more years of experience in data science, analytics, or decision science, including at least three years managing and developing a team.

• A 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, and the judgment to know which one a problem calls for.

• Strong SQL skills, plus fluency in Python or R.

• Experience with modern data platforms and large-scale data tools, such as Snowflake, Databricks, or Spark.

• The ability to explain a complicated analysis to an executive in plain language, and to defend the method to a peer who knows the math.

• A record of hiring well, developing people, and building a team culture others want to join.

• Comfort setting priorities in a fast-moving environment where the questions change and the data is imperfect.

• A master's or PhD in statistics, economics, computer science, operations research, applied mathematics, or a related quantitative field, or equivalent practical experience.

Nice to have.

• Experience in education technology or another B2B SaaS business.

• Familiarity with subscription and product-led growth metrics, such as retention, expansion, and adoption.

• Experience building an analytics or decision science function from an early stage.