Decision Science Intern at Instructure in Location not listed

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: Instructure, Inc. is seeking a motivated Decision Science Intern to support our data-driven initiatives. This role involves applying analytical techniques to real-world problems, contributing to product and business strategy, and gaining hands-on experience in a fast-paced technology company. Job Responsibilities * Assist in the collection, cleaning, and preparation of large datasets for analysis. * Conduct exploratory data analysis to identify trends, patterns, and insights. * Develop and implement statistical models and machine learning algorithms to solve business problems. * Contribute to the design and analysis of A/B tests and other experimental methodologies. * Visualize and communicate analytical findings to both technical and non-technical stakeholders. * Collaborate with product managers, engineers, and other data professionals to understand business needs and deliver actionable recommendations. * Support the development and maintenance of data pipelines and analytical tools. * Participate in team meetings and contribute to ongoing learning and knowledge sharing. Job Qualifications * Currently pursuing a Bachelor's, Master's, or Ph.D. degree in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, Operations Research, or a related discipline. * Strong understanding of statistical concepts and methods. * Proficiency in at least one programming language commonly used for data analysis (e.g., Python, R). * Familiarity with SQL for data extraction and manipulation. * Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, ggplot2) is a plus. * Excellent analytical and problem-solving skills. * Strong communication and interpersonal skills, with the ability to explain complex findings clearly. * Ability to work independently and as part of a team in a dynamic environment. * Prior experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) is a bonus. 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.