Portfolio Data Analyst

• The Global Product Organization (GPO) is defining the future of safety and security technologies
• This role sits within the Strategic Portfolio Management (SPM) team of the Unified Communications (UC) Group
• We are unifying siloed voice and data networks into an ecosystem that provides actionable intelligence for end users while fostering an outcome-driven product culture where success is measured by how precisely we solve pervasive market problems
• We are seeking an analytical growth architect to bridge the gap between market reality, advanced data infrastructure, and executive strategy
• Operating at the structural intersection of Product Development, Sales Operations (RevOps), Data Science, and Strategic Finance, you will focus on utilizing data sources and AI tools for both holistic and product specific business intelligence
• In this role, you will move beyond retrospective reporting to build automated strategic foresight and predictive decision engines
• Predictive Machine Learning & Advanced Data Engineering
• Stochastic Risk Engineering & Code Development: Write production-grade code to build data pipelines and provide portfolio performance updates
• Automated Decision Engines: Architect “Sense-Decide-Act-Learn” operational loops, incorporating agent-driven AI tools to automate complex data synthesis in near real-time
• Financial & Monetization Modeling: Develop ad-hoc cost-benefit analyses, SKU attach rates, and competitive assessments to support product planning, roadmap prioritization, and high-margin innovations
• Data Visualization & Intelligence Democratization
• Democratizing Intelligence: Act as an enablement specialist by integrating self-service AI and natural language tools that allow non-technical stakeholders to converse with data
• Metric Governance & Data Quality: Serve as a system data expert across platforms using SQL, ensuring data integrity, defining KPIs, and optimizing data architecture
• Scalable Dashboards: Build, modify, and maintain interactive dashboards to enable deep visibility into feature usage and associated cloud cost drivers
• Strategic Opportunity Valuation & Foresight
• Strategic Prioritization: Evaluate and monitor timelines of key initiatives, ensuring key dates are met with the corresponding deliverable or business actions
• Predictive Foresight & Value-Add Discovery: Proactively discover and quantify the ROI of new feature opportunities, leverage predictive models to anticipate competitive shifts, market changes, and customer behaviors
• Competitive Intelligence: Maintain a granular understanding of competitive features, availability, and emerging technology across the industry

Benefits

• Flexible work models
• Paid time off
• Paid parental and family leave
• Health care benefits
• Global wellness resources
• Employee assistance programs
• Rotation programs
• Mentor relationships
• Learning and development opportunities
• Retirement benefits
• Employee bonuses
• Stock grants & employee stock purchase plans

• Proficiency in SQL for complex data extraction and platform integration
• Advanced Python development for data manipulation and machine learning (NumPy, Pandas, SciPy, Scikit-learn)
• Proficiency with data visualization tools (Tableau or Power BI) and complex financial modeling in Excel
• Experience: 2 to 4 years of experience as a data analyst, financial analyst, strategy analyst, or in a product growth/management consulting role within SaaS or high-growth tech environments
• Education: Bachelor’s degree in Economics, Business Analytics, Data Science, Finance, STEM, or a related quantitative field
• If you’d like to join our team but feel that you don’t quite meet all of the preferred skills, we’d still love to hear why you think you’d be a great addition to our team
• Prior experience in top-tier management consulting, corporate strategy, or Revenue Operations (RevOps) in B2B/SaaS
• Demonstrated “Scientific Tinkerer” mindset, possessing deep intellectual curiosity, rigorous hypothesis testing habits, and comfort operating in fast-paced, high-ambiguity environments
• MBA or Master’s degree in Data Science, Financial Engineering, or Strategic Portfolio Management