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Associate Data Scientist, AI & Analytics

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Instructure

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Location:
Hungary , Budapest

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Contract Type:
Not provided

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Salary:

1000000.00 - 14000000.00 HUF / Month

Job Description:

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: We believe in empowering people through data, and we’re looking for a Decision Scientist to help us uncover insights that drive better learning experiences and strategic outcomes. As an Associate Data Scientist at Instructure, you’ll work at the intersection of data, AI, and business decision-making. You’ll partner closely with senior Data Scientists, product managers, and cross-functional teams to support analyses that inform product, growth, and go-to-market decisions impacting millions of learners. This role is designed for early-career Data Scientists who have strong analytical foundations, hands-on project experience, and high learning velocity, and who are ready to grow into owning end-to-end work with mentorship and support.

Job Responsibility:

  • Support cross-functional projects by translating business questions into analytical work, including exploratory analysis, experimentation support, and modeling
  • Analyze product and user data to surface insights related to feature performance, engagement, and growth
  • Build and maintain dashboards, reports, and analyses that help teams understand key metrics
  • Contribute to experimentation efforts (A/B tests), including setup, analysis, and interpretation
  • Assist with forecasting and modeling used for planning and decision-making
  • Communicate findings through clear written summaries, visualizations, and presentations
  • Use AI tools (e.g., ChatGPT, Claude, Cursor) to accelerate analysis, coding, and learning
  • Learn and apply best practices around data quality, experimentation, and statistical rigor
  • Contribute to a culture of learning, documentation, and continuous improvement within the data team

Requirements:

  • 0–2 years of experience in data science, analytics, or a related quantitative role (or strong recent graduates with meaningful applied experience)
  • Strong foundations in SQL and experience using Python or R for analysis
  • Coursework or hands-on experience with: Statistics and experimentation
  • Core machine learning techniques (e.g., regression, classification, clustering, time series)
  • Practical experience through internships, research, coursework projects, or side projects
  • Comfort working with messy, real-world data
  • Familiarity with BI and data visualization tools (e.g., Tableau, Looker, Power BI)
  • Experience using AI tools to accelerate analysis and problem solving
  • Clear communication skills and willingness to ask questions, learn, and iterate
  • Curiosity, adaptability, and strong learning velocity

Nice to have:

  • Experience in EdTech or working with education-related products
  • Familiarity with cloud-based data platforms (e.g., Snowflake, Redshift, BigQuery)
  • Experience with product analytics, experimentation, or lifecycle analysis
  • Prior experience working in cross-functional teams
What we offer:
  • 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

Additional Information:

Job Posted:
January 15, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
Job Link Share:

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