Jobs / United States / Instructure

Instructure

Director, Decision Science

Remote (USA) · Remote · US only Posted today

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Skills this job asks for

Product managementLeadershipStatisticsMachine learningSQLPythonSnowflakeSparkB2B sales

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Where you can work from

United States only

Based on the listing's location: Remote (USA).

The company's headquarters is not the same as where you may work from. Visa sponsorship only matters if you would relocate; see below.

Visa sponsorship, if you would relocate

Sponsorship verdict

No sponsorship evidence yet

No government record and no wording either way. Not a refusal: ask the recruiter.

  • No government sponsor record hereThis employer posted directly and does not match a government sponsor register.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • What Instructure paid sponsored hires in similar roles1 certified filing for “Principal Decision Scientist” (Data Scientists) in CA: $200k–$200k, median $200k.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
What Instructure paid sponsored hires in similar roles
1 certified filing for “Principal Decision Scientist” (Data Scientists) in CA: $200k–$200k, median $200k. Most were filed at wage level IV (100%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.

Before you apply

Sponsorship unknown

No register record and no sponsorship wording in the posting. Worth asking the employer before investing significant time.

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About the 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: 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. • 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

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