Principal 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 Principal Decision Scientist at Instructure will play a key role in elevating how data informs strategic decisions across the organization in an AI first era. As a technical leader within our newly formed Decision Science group, you will partner closely with product, engineering, marketing, and executive leadership to identify high-impact opportunities, design rigorous experimentation frameworks, and deliver predictive insights that drive measurable business value across the Canvas LMS and broader Instructure ecosystem.

This is a high-visibility opportunity to help build and shape a modern decision science capability at scale. You will help establish best practices for experimentation, causal analysis, and advanced analytics while mentoring other data scientists and analysts and influencing how data guides product innovation and business growth.

Impact of the Role

As a Principal Decision Scientist, you will help define how data informs decisions across Instructure. You will play a foundational role in shaping the company’s decision science capabilities—driving experimentation, influencing product strategy, providing recommendations to further business outcomes and unlocking the value of Instructure’s data to power innovation across the learning ecosystem.

In this role, you will:

• Drive business impact through data-driven insights

• Identify high-value opportunities to improve product adoption, customer engagement, and revenue growth through advanced analytics and predictive modeling

• Default to AI first thinking to design analysis, recommend solutions, elevate standards/throughput on the team

• Lead experimentation and causal analysis

• Design and execute rigorous A/B tests and causal inference studies to evaluate the impact of new product features, marketing strategies, and operational initiatives

• Influence product and business strategy

• Partner with product managers, engineers, marketing leaders, and executives to translate complex business questions into analytical approaches that inform strategic decisions

• Deliver end-to-end analytical solutions

• Own the full lifecycle of analytical initiatives—from identifying opportunities and building models to partnering with business teams to drive adoption and measurable impact

• Establish decision science best practices

• Serve as a technical leader within the Decision Science organization by defining standards for experimentation, modeling, and analytical rigor

• Mentor and elevate the analytics community

• Guide and mentor data scientists and analysts across the organization by demonstrating best practices in technical execution and business partnership

• Advance analytics and AI capabilities

• Explore emerging analytics and AI technologies to unlock new insights and help evolve Instructure’s data and decision-making capabilities

• Communicate insights clearly and effectively

• Translate complex analytical findings into actionable recommendations for both technical and non-technical stakeholders

What you will need to know / have

• PhD or Master's degree in Statistics, Computer Science, Economics, Applied Mathematics, Operations Research, or a related quantitative field

• 8+ years of experience in data science, analytics, or a related discipline with a track record of delivering measurable business impact

• Expertise in statistical modeling, machine learning, causal inference, and experimental design (A/B testing)

• Deep familiarity with AI tooling (Claude/ChatGPT/Glean) to improve throughput

• Strong proficiency in SQL for data extraction and manipulation

• Proficiency in Python or R for data analysis, modeling, and visualization

• Experience working with modern data platforms (e.g., Snowflake, Databricks, fivetran)

• Strong communication and storytelling skills with the ability to translate complex analyses into clear recommendations

• Demonstrated ability to lead end-to-end data science initiatives from problem definition through deployment and impact measurement

• Experience working in SaaS, product analytics, or EdTech environments is a plus

• Ability to operate independently while collaborating effectively in a fast-paced, cross-functional environment

Get in on all the awesome at Instructure!

We offer competitive, meaningful benefits in every country where we operate. While they vary by location, here's a general idea of what you can expect:

• Competitive compensation, plus all full-time employees participate in our ownership program - because everyone should have a stake in our success.

• Flexible work culture. Our remote, hybrid and in-office collaboration spaces vary by role, team and location.

• Generous time off, including local holidays and our annual “Dim the Lights” period in late December, when teams are encouraged to step back and recharge based on departmental needs.

• Comprehensive wellness programs and mental health support

• Annual learning and development stipends to support your growth

• The technology and tools you need to do your best work

• Motivosity employee recognition program

• A culture rooted in inclusivity, support, and meaningful connection

We believe in hiring great people and treating them right. The more diverse we are, the better our ideas and outcomes.

Instructure is an Equal Opportunity Employer. We comply with applicable employment and anti-discrimination laws in every country where we operate.

All employees must pass a background check as part of the hiring process. To help protect our teams and systems, we’ve implemented identity verification measures. Candidates may be asked to verify their legal name, current physical location, and provide a valid contact number and residential address, in accordance with local data privacy laws.

Any attempt to misrepresent personal or professional information will result in disqualification.