JobsMotorola Solutions

Portfolio Data Analyst

Motorola Solutions · Chicago, IL

Posted Aug 19, 2026 · We last checked this listing on Sep 20, 2026

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Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

Behavioral

Tell me about a time you had to explain a complex analysis to someone non-technical, maybe a sales or executive stakeholder, who needed to act on it quickly.

ability to democratize intelligence for non-technical audiences, a core stated responsibility

Tell me about a dashboard you built that people actually kept coming back to, versus one that got ignored. What was the difference?

understanding of what drives dashboard adoption, not just technical construction

Describe a time your predictive model or forecast turned out to be wrong. What did you do next?

intellectual honesty and the 'rigorous hypothesis testing' mindset the posting explicitly wants

Tell me about a time you had to push back on a finance, sales, or product stakeholder because your data told a different story than they expected.

stakeholder management and willingness to defend data-driven conclusions across functions

This role sits between product, sales operations, data science, and finance. Tell me about a time you had to reconcile conflicting priorities from different functions on a single analysis or project.

ability to operate at cross-functional structural intersections, which the posting explicitly frames as central to the job

Technical

Walk me through a data pipeline you built end to end, from raw source to something a business leader used to make a decision.

whether the candidate has actually shipped production-grade code, not just analysis in notebooks

Say you're given access to SKU attach rate data across a product portfolio. How would you go about building a model to identify which SKUs are underperforming and why?

depth of financial and monetization modeling skill, and whether they think in business terms, not just statistical ones

What's your experience with agent-driven AI tools or natural language interfaces over data, and can you give an example of building or integrating one?

real hands-on experience with the specific AI-enablement tools mentioned, versus general AI familiarity

If you had to write a SQL query to reconcile feature usage data with cloud cost data across multiple platforms, and the join keys didn't quite line up, how would you approach it?

practical SQL and data integrity troubleshooting skill under messy real-world conditions

What Python libraries do you reach for when building a machine learning model from scratch, and can you walk through a specific project where you used scikit-learn or SciPy for something beyond a basic regression?

actual depth versus surface familiarity with the named tools

Situational

How would you design a 'Sense-Decide-Act-Learn' loop for something like tracking a competitor's new feature launch?

whether the candidate can translate the posting's own conceptual framework into a concrete, workable system rather than buzzwords

Imagine you're asked to quantify the ROI of a new feature that has no historical usage data yet. How would you build that estimate?

comfort with ambiguity and ability to construct defensible estimates from limited data

How do you decide which KPIs actually matter when a portfolio has dozens of products and everyone wants their own metric tracked?

judgment around metric governance and prioritization in a multi-product environment

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The full job description

As published by Motorola Solutions.

Company Overview At Motorola Solutions, we believe that everything starts with our people. We’re a global close-knit community, united by the relentless pursuit to help keep people safer everywhere. We build and connect technologies to help protect people, property and places. Our solutions foster the collaboration that’s critical for safer communities, safer schools, safer hospitals, safer businesses, and ultimately, safer nations. Connect with a career that matters, and help us build a safer future. Department Overview 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. Job Description 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 Technical Skills: • 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 Preferred Qualifications • 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 Basic Requirements • Education : Bachelor’s degree in Economics, Business Analytics, Data Science, Finance, STEM, or a related quantitative field • 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 Travel Requirements None Relocation Provided None Position Type Experienced Referral Payment Plan No Our U.S. Benefits include: • Incentive Bonus Plans • Medical, Dental, Vision benefits • 401K with Company Match • 10 Paid Holidays • Generous Paid Time Off Packages • Employee Stock Purchase Plan • Paid Parental & Family Leave • and more! EEO Statement Motorola Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion or belief, sex, sexual orientation, gender identity, national origin, disability, veteran status or any other legally-protected characteristic.  We are proud of our people-first and community-focused culture, empowering every Motorolan to be their most authentic self and to do their best work to deliver on the promise of a safer world. 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. We’re committed to providing an inclusive and accessible recruiting experience for candidates with disabilities, or other physical or mental health conditions. To request an accommodation, please complete this  Reasonable Accommodations Form  so we can assist you.

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