Portfolio Data Analyst

Motorola Solutions•Chicago, IL

18h•Onsite

About The Position

Motorola Solutions is seeking an analytical growth architect to bridge the gap between market reality, advanced data infrastructure, and executive strategy. This role operates at the intersection of Product Development, Sales Operations (RevOps), Data Science, and Strategic Finance, focusing on utilizing data sources and AI tools for both holistic and product-specific business intelligence. The goal is to move beyond retrospective reporting to build automated strategic foresight and predictive decision engines.

Requirements

Bachelor’s degree in Economics, Business Analytics, Data Science, Finance, STEM, or a related quantitative field.
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.
Advanced Python development for data manipulation and machine learning (NumPy, Pandas, SciPy, Scikit-learn).
Proficiency in SQL for complex data extraction and platform integration.
Proficiency with data visualization tools (Tableau or Power BI) and complex financial modeling in Excel.

Nice To Haves

MBA or Master's degree in Data Science, Financial Engineering, or Strategic Portfolio Management.
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.

Responsibilities

Write production-grade code to build data pipelines and provide portfolio performance updates.
Architect "Sense-Decide-Act-Learn" operational loops, incorporating agent-driven AI tools to automate complex data synthesis in near real-time.
Develop ad-hoc cost-benefit analyses, SKU attach rates, and competitive assessments to support product planning, roadmap prioritization, and high-margin innovations.
Integrate self-service AI and natural language tools that allow non-technical stakeholders to converse with data.
Serve as a system data expert across platforms using SQL, ensuring data integrity, defining KPIs, and optimizing data architecture.
Build, modify, and maintain interactive dashboards to enable deep visibility into feature usage and associated cloud cost drivers.
Evaluate and monitor timelines of key initiatives, ensuring key dates are met with the corresponding deliverable or business actions.
Proactively discover and quantify the ROI of new feature opportunities, leverage predictive models to anticipate competitive shifts, market changes, and customer behaviors.
Maintain a granular understanding of competitive features, availability, and emerging technology across the industry.