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 Principal Decision Scientist at Instructure will play a key role in elevating how data informs strategic decisions across the organization in an AI first era. As a technical leader within our newly formed Decision Science group, you will partner closely with product, engineering, marketing, and executive leadership to identify high-impact opportunities, design rigorous experimentation frameworks, and deliver predictive insights that drive measurable business value across the Canvas LMS and broader Instructure ecosystem. This is a high-visibility opportunity to help build and shape a modern decision science capability at scale. You will help establish best practices for experimentation, causal analysis, and advanced analytics while mentoring other data scientists and analysts and influencing how data guides product innovation and business growth. Impact of the Role As a Principal Decision Scientist, you will help define how data informs decisions across Instructure. You will play a foundational role in shaping the company’s decision science capabilities—driving experimentation, influencing product strategy, providing recommendations to further business outcomes and unlocking the value of Instructure’s data to power innovation across the learning ecosystem. In this role, you will: - Drive business impact through data-driven insights - Identify high-value opportunities to improve product adoption, customer engagement, and revenue growth through advanced analytics and predictive modeling - Default to AI first thinking to design analysis, recommend solutions, elevate standards/throughput on the team - Lead experimentation and causal analysis - Design and execute rigorous A/B tests and causal inference studies to evaluate the impact of new product features, marketing strategies, and operational initiatives - Influence product and business strategy - Partner with product managers, engineers, marketing leaders, and executives to translate complex business questions into analytical approaches that inform strategic decisions - Deliver end-to-end analytical solutions - Own the full lifecycle of analytical initiatives—from identifying opportunities and building models to partnering with business teams to drive adoption and measurable impact - Establish decision science best practices - Serve as a technical leader within the Decision Science organization by defining standards for experimentation, modeling, and analytical rigor - Mentor and elevate the analytics community - Guide and mentor data scientists and analysts across the organization by demonstrating best practices in technical execution and business partnership - Advance analytics and AI capabilities - Explore emerging analytics and AI technologies to unlock new insights and help evolve Instructure’s data and decision-making capabilities - Communicate insights clearly and effectively - Translate complex analytical findings into actionable recommendations for both technical and non-technical stakeholders What you will need to know / have - PhD or Master's degree in Statistics, Computer Science, Economics, Applied Mathematics, Operations Research, or a related quantitative field - 8+ years of experience in data science, analytics, or a related discipline with a track record of delivering measurable business impact - 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 - 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 recommendations - Demonstrated ability to lead end-to-end data science initiatives from problem definition through deployment and impact measurement - Experience working 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 - Annual learning and development stipends to support your growth - The technology and tools you need to do your best work — typically a Mac, with PC options available in some locations - 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.

• Own the analytical agenda — define which problems are worth pursuing, set the criteria for feasibility, and establish how the team evaluates project viability. • Set the standard for analytical communication across the team — defining templates, review processes, and quality bars for how insights are documented and shared in Jupyter or Colab notebooks. • Drive alignment across product, engineering, and leadership on data strategy — proactively surfacing gaps and influencing roadmap decisions to address them. • Lead the modeling strategy for pricing and bidding — defining the technical approach across the stack (scikit-learn, statsmodels, TensorFlow, PyTorch), evaluating tradeoffs, and being accountable for measurable business outcomes. • Prototype predictive models that can be scaled by the ML engineering team into production systems. • Leverage Vertex AI or equivalent tools for experimentation, training, and deployment workflows. • Create visualizations using Python (Plotly, Matplotlib, or Seaborn) to communicate key findings effectively. • Contribute to a culture of analytical rigor, documentation, and rapid experimentation.

• Partner with Engineering and Business teams to seamlessly integrate models into our recommendation engine. • Drive the full lifecycle of our yield optimization models, from ideation and development to production monitoring and iteration. • Continuously evaluate and improve model accuracy and interpretability to directly impact key business KPIs like revenue and conversion rates. • Use sophisticated models to intelligently match users to the best offers, driving value for our internal agency and external buyers. • Interface directly with external partners, ensuring mutual success and aligning model performance with partner goals.

For decades, DTN has been the silent force behind some of the world’s most critical industries—helping businesses navigate complexity, uncertainty, and risk with smarter, faster decisions. From agriculture to energy to weather intelligence, our proprietary Operational Decisioning Platform transforms raw data into decision-grade insights—enabling companies to optimize supply chains, ensure market stability, and safeguard infrastructure against disruption. We don’t follow trends—we set the standard for precision, trust, and operational impact. DTN is at an exciting inflection point. Building off a foundation of financial strength, profitability, and industry trust, we’re accelerating growth and expanding our global footprint. Our purpose-built solutions—powered by AI and honed by decades of vertical expertise—are helping some of the world’s most significant enterprises thrive amid operational constraints and uncover new opportunities in a fast-changing world. Job Description: Position Summary: DTN is seeking a Senior Data Scientist to lead the development and deployment of advanced analytics, machine learning, and predictive modeling solutions that drive business insights and product innovation. This role partners closely with cross-functional teams to translate complex data into actionable outcomes, while guiding data science initiatives from concept through production. The ideal candidate brings deep technical expertise, strong business acumen, and the ability to lead and mentor others in a collaborative environment. What You Will Be Responsible For: - Lead initiatives leveraging data mining, statistical analysis, and advanced modeling techniques to generate business insights. - Design, implement, and validate predictive and prescriptive models to support product and customer outcomes. - Partner with cross-functional stakeholders to understand business needs and determine appropriate modeling approaches. - Conduct feasibility studies and exploratory analyses to evaluate data science hypotheses and opportunities. - Develop dashboards, reports, and visualizations to communicate model outputs and insights to stakeholders. - Represent DTN data science in customer interactions, discovery sessions, and internal presentations. - Mentor and lead a small team of data scientists, fostering best practices and continuous improvement. What You Will Bring to the Position: - Strong professional experience in machine learning, predictive modeling, and statistical analysis. - Proficiency in Python and scientific computing libraries such as pandas, NumPy, scikit-learn, and related tools. - Experience with data visualization tools and libraries such as matplotlib, Plotly, or similar frameworks. - Experience building dashboards using tools such as Dash, Streamlit, or equivalent platforms. - Experience training, retraining, and maintaining predictive models in production environments. - Proven ability to lead data science initiatives and collaborate with cross-functional stakeholders. - Strong communication skills with the ability to present complex data insights to technical and non-technical audiences. What You Can Expect from DTN: - Competitive Salary - Unlimited PTO - Flexible working hours - Remote work model (position dependent) - Competitive Medical, Dental and Vision Insurance Plans - 6% 401K matching - Unlimited access to 13k+ courses via learning platform to support employee career advancement - Employee Assistance Program (EAP) Compensation: The targeted hiring base pay range for this position is between $123,500 and $164,500. DTN is a pay-for-performance organization, which means there is the opportunity to advance your compensation with performance over time. The actual base pay offered for this position will be dependent upon many factors, including but not limited to: prior work experience, training/education, transferable skills, business needs, internal equity and applicable laws. The targeted hiring base pay range is subject to change and may be modified in the future. This role may also be eligible for market competitive variable pay and benefits. #LI-remote #LI-TH1 About DTN: DTN is a global data and technology company helping operational leaders in energy, agriculture, and weather-driven industries make faster, smarter decisions. Our Operational Decisioning Platform turns complex data into decision-grade insights—empowering customers to expand their margins, accelerate growth, and outpace risk. With more than 1,200 employees globally, DTN serves the companies that feed, fuel, and protect the world. At DTN, we value clarity, trust, and action. We’re a team of problem-solvers, outcome-drivers, and industry nerds who believe that precision matters – and that mission is at the core of what we do. - Trust Built: We earn it. We keep it. We protect it. Our neutrality, precision, and integrity are non-negotiable. - Confidence-Driven: We help customers move with clarity and conviction. We bring the data and operational knowledge leaders need to act. - Built for Industry: We speak operations because we come from operations. Our expertise is forged in fuel terminals, fields, flight paths, and forecasts. - Future-Forward: We see what’s coming- and we’re ready. We help customers lead through change with smarter decisioning. Recruitment Fraud Notice: DTN is aware of incidents where external parties have impersonated our organization, issuing fraudulent communications and/or job offers. Please be advised that all legitimate communication from DTN will come from an official @dtn.com email address or through our Paradox AI automated scheduling platform (Talent IQ). Any offers are extended directly by our Talent Acquisition team following a formal interview process. If you receive a suspicious message or offer claiming to be from DTN, please do not engage. Contact our Talent Acquisition team at Careers@dtn.com to verify the legitimacy of any communication. Report any fraudulent messaging as phishing or spam. DTN is an Equal Opportunity Employer. We welcome and encourage applicants of all backgrounds, including minorities, women, veterans, and individuals with disabilities.