Original listing text, shown exactly as published by the company.
What you will do
- Drive business impact through data-driven insights. Identify and pursue high-value opportunities to improve product adoption, customer engagement, and revenue growth using advanced analytical and statistical methods.
- Lead experimentation and causal analysis. Design and execute rigorous A/B tests and causal inference studies to evaluate the impact of new product features, pricing strategies, and go-to-market initiatives. Champion experimental rigor across teams.
- Influence product and business strategy. Partner with product managers, engineers, marketing leaders, and senior stakeholders to translate complex business questions into structured analytical frameworks and deliver strategic recommendations.
- Deliver end-to-end analytical solutions. Own the full lifecycle of analytical initiatives — from identifying opportunities and building models to deploying solutions and measuring impact.
- Default to AI-first thinking. Design analysis approaches, recommend solutions, and elevate standards and throughput across the team by leveraging AI tooling and modern analytical techniques.
- Contribute to decision science best practices. Help define standards for experimentation, modeling, and insight delivery that raise the bar for analytical quality across the organization.
- Mentor and elevate peers. Guide data scientists and analysts by demonstrating best practices in methodology, communication, and stakeholder engagement.
- Communicate insights clearly and effectively. Translate complex analytical findings into actionable recommendations for both technical and non-technical audiences, including executive leadership.
What you will need to know/have
- Master's degree or PhD in Statistics, Computer Science, Economics, Applied Mathematics, Operations Research, or a related quantitative field.
- 5–7 years of experience in data science, analytics, or a related discipline with a track record of delivering high-impact, cross-functional insights.
- 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 and analytical quality.
- 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, strategic narratives.
- Demonstrated ability to lead end-to-end data science initiatives from problem definition through deployment and measurement.
- Experience 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
- Learning and development resources, including professional development tools and tuition reimbursement, 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.
