Data Scientist II

Job Description  At Infoblox, every breakthrough begins with a bold “what if.” What if your ideas could ignite global innovation? What if your curiosity could redefine the future? We invite you to step into the next exciting chapter of your career journey. Bring your creativity, drive, your daring spirit, and feel what it’s like to thrive on a team big enough to make an impact, yet small enough to make a difference.

Our cloud-first networking and security solutions already protect 70% of the Fortune 500, and we’re looking for creative thinkers ready to push that influence even further. Join us and discover how far your bold “what if” can take the world, your community, and your career. How we empower our people is extraordinary: we’re recognized as a Glassdoor Best Place to Work 2025, Great Place to Work-Certified in five countries, and honored by Cigna as a Healthy Workforce honors for three consecutive years;

and what we build is world class: named Cybersec Asia’s Best in Critical Infrastructure 2024 — clear evidence that when first-class technology meets empowered talent, remarkable careers take shape. So, what if the next big idea, and the next great career story, comes from you? Become the force that turns every “what if” into “what’s next.” In a world where you can be anything, Be Infoblox.
Data Scientist II  We have an opportunity for a Data Scientist to join our Business Strategy team in Burnaby, Canada, reporting to the Director, Business Strategy. In this pivotal role, you will turn complex business questions into clear, data-driven insights and decision frameworks that shape Infoblox’s company strategy, growth programs, and executive operating rhythms. Collaborating closely with Business Strategy, Finance, Product, Go-to-Market, and Data & AI teams, you will build forecasting models, customer lifecycle analytics, and AI-powered decision support that help leaders make faster, higher-confidence decisions on where and how to invest.
Be a Contributor — What You’ll Do   Translate executive and strategy questions into structured analytical problems, hypotheses, and measurable success metrics tied to Infoblox’s strategic pillars, strategic programs, annual objectives and key results
Build, validate, and maintain statistical and machine learning models (e.g., churn and upsell propensity, pipeline health, segmentation, etc.) to inform planning and portfolio choices
Create scenario planning, sensitivity, and what-if analysis frameworks that help leaders evaluate trade-offs across revenue growth, margin, investment, and risk
Design and operationalize KPI definitions, metric hierarchies, and data quality checks in partnership with domain data owners to ensure a single source of truth for executive and board-level reporting
Partner with data engineering and analytics teams to shape semantic models, data products, and feature stores that enable robust, reusable decision science assets
Use AI and GenAI tools (e.g., AI-assisted coding, GenAI copilots, RAG-based knowledge search) to accelerate analysis, automate recurring workflows, and build decision-support prototypes, following Infoblox’s responsible AI guardrails
Design and analyze experiments (A/B tests, pilots, quasi-experiments) with Product, Marketing, and Sales to quantify the impact of strategic initiatives
Develop clear, executive-ready narratives, visualizations, and recommendations that connect advanced analytics to business implications and concrete actions for Infoblox leadership
Champion data literacy and AI adoption across the Business Strategy organization by sharing reusable assets, playbooks, and training on decision science and AI-powered decision support
Be Prepared — What You Bring   5–8 years of experience in data science, decision science, or advanced analytics with a focus on business strategy, finance, product, or go-to-market problems in B2B technology or SaaS environments (or equivalent combination of education and experience)
Demonstrated expertise with statistical modeling and machine learning techniques relevant to strategy and planning (e.g., time series forecasting, regression, classification, clustering, scenario…