Own cross-functional analytics initiatives by translating product and growth objectives into end-to-end analytical workflows, including exploratory analysis, experiment design, modeling, and interpretation
Design, execute, and evaluate experiments (A/B tests) to assess feature performance, marketing impact, and user behavior
Perform large-scale data analysis to extract insights and support product and business decision-making.
Develop and validate machine learning models using core techniques such as regression, classification, clustering, and time series to solve business problems.
Build predictive and forecasting models that support product planning, business strategy, and decision-making
Identify leading indicators and define metrics that enable teams to track progress and outcomes
Build and deliver dashboards, reports, and data products that provide visibility into product and user behavior
Communicate insights clearly and persuasively to executive and functional stakeholders using both data and storytelling
Partner with data engineering to improve data pipelines, reliability, and access at scale
Use AI tools (e.g., ChatGPT, Claude, Cursor, Windsurf) to accelerate analysis, coding, and insight generation
Contribute to a culture of learning, experimentation, documentation, and continuous improvement within the data organization
Mentor and support junior Data Scientists through feedback, guidance, and shared best practices

Requirements

3–6+ years of experience in data science, analytics, or a related quantitative role
Strong proficiency in SQL and experience using Python or R for analysis and modeling
Deep knowledge of: experimentation and A/B testing, statistical methods and causal inference, core machine learning techniques (e.g., regression, classification, clustering, time series)
Proven experience owning analyses or models used to inform real business or product decisions
Experience working with large, messy datasets in production environments
Strong familiarity with BI and data visualization tools (e.g., Tableau, Looker, Power BI)
Demonstrated ability to distill complex analyses into clear, actionable insights
Comfort navigating ambiguity and prioritizing work in a fast-paced, evolving environment
Strong communication skills and ability to collaborate effectively with technical and non-technical stakeholders
Experience leveraging AI tools (e.g., ChatGPT, Claude, Cursor, Windsurf) to accelerate analysis, coding, insight generation, and improve overall productivity of analytical workflows

Benefits

Competitive compensation and participation in Instructure’s equity program
Flexible schedules and a remote-friendly culture, with hybrid or onsite work based on business needs
Annual “Dim the Lights” company-wide shutdown from December 26 to December 31
Comprehensive wellness programs and mental health support
Annual learning and development stipends to support your growth
We provide the technology and tools you need to do your best work—typically a Mac, with PC options available in some locations
A culture rooted in inclusivity, support, and meaningful connection

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

data analysismachine learningregressionclassificationclusteringtime seriesA/B testingstatistical methodsSQLPython

communicationcollaborationmentoringproblem-solvingstorytellingadaptabilityanalytical thinkingattention to detailcreativityleadership