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Senior Decision Scientist

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Remote from
Mexico
Salary
MXN 911k–1,100k / yr
Employment
Full Time
Experience
Director
Published
Apply before
12 Nov 2026
Listing views
140
Application actions
9
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AI Summary

The role, at a glance.

Instructure is seeking a Senior Decision Scientist to lead high-impact analytical initiatives that improve product adoption, customer engagement, pricing, and revenue outcomes. The role centers on statistical modeling, machine learning, causal inference, and rigorous experimentation such as A/B testing. This person will partner with product, engineering, marketing, and executive stakeholders to turn complex questions into strategic recommendations. They will own analytics work from opportunity definition through deployment and impact measurement while promoting AI-enabled analytical practices. The position also includes mentoring peers and establishing stronger decision-science standards across the organization.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is a senior, end-to-end data science role requiring advanced causal methodology, experimentation expertise, technical fluency, and demonstrated business impact. The role also demands independent prioritization and the ability to influence senior cross-functional stakeholders with clear strategic narratives.

Salary analysis

Estimated compensation compared with the broader MXN market for similar roles.

Estimated job median (per year)
MXN1,005,500
MXN market range (period not specified)MXN900k–MXN1,250k
AI insightSalary comparison is unavailable: the pay periods are unspecified or differ, or salary amounts are unavailable. Market figures are AI estimates. Regenerate the analysis to obtain a market estimate with an explicit period.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
Describe an A/B test you designed for a product or commercial decision. How did you determine whether the result was reliable?

I would begin by defining the decision, primary metric, guardrail metrics, target population, and expected effect size. I would calculate sample-size requirements, validate randomization and instrumentation, analyze results with confidence intervals and practical-impact thresholds, and check for segment-level effects before recommending a rollout, iteration, or further testing.

How would you assess the impact of a product feature when a randomized experiment is not feasible?

I would first clarify the treatment assignment process and available pre- and post-treatment data. Depending on the setting, I could use methods such as difference-in-differences, matching, regression discontinuity, interrupted time series, or synthetic controls, while testing assumptions and communicating residual limitations clearly.

A product leader says engagement has fallen and wants an immediate explanation. How would you approach the problem?

I would align on the engagement definition, affected users, timeframe, and recent changes, then segment the trend by cohort, platform, geography, plan type, and key product behaviors. I would validate data quality, identify the largest contributors to the decline, formulate testable hypotheses, and present prioritized actions with expected impact and confidence levels.

How do you make complex analytical findings actionable for executive stakeholders?

I lead with the business decision, the quantified impact, and the recommended action rather than the technical detail. I use a concise narrative supported by clear visuals, explain uncertainty in plain language, and retain methodological documentation for audiences that need a deeper review.

How have you used AI tools while maintaining analytical rigor and data governance?

I use AI tools to accelerate tasks such as exploratory analysis, code drafting, documentation, and idea generation, but I independently validate outputs, protect sensitive data, and maintain reproducible workflows. Any model-generated recommendation is checked against source data, statistical assumptions, business context, and organizational privacy standards before it informs a decision.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

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:

As a Senior Decision Scientist, you will drive meaningful business outcomes by leading complex analytical initiatives and serving as a trusted partner to senior stakeholders.

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.

Apply now >

This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

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