Print Supplies Big Data Analyst

• Own and support monthly validation processes for print telemetry outputs, dashboard semantic layers, and related usage/share reporting handoffs

• Serve as a key analytical partner for Forecasting and business stakeholders, helping answer usage, share, installed base, product readiness, and release approval questions through structured analysis and clear communication

• Develop and maintain automated and well-documented processes that support recurring validation, issue diagnosis, data quality checks, and stakeholder decision-making

• Conduct root-cause analysis on data discrepancies across sources, grains, tables, dashboards, and processing layers, especially where definitions, filters, platform coverage, or reporting timing create mismatches

• Provide consultative support for quick-turn ad hoc requests, escalation support, and deep-dive investigations while helping route work through the appropriate intake, prioritization, and transition processes

• Collaborate with dashboard, data engineering, and business intelligence partners to improve transparency, repeatability, and maintainability of analytics outputs
• Provides guidance and mentoring to less- experienced staff members
• Applies advanced subject matter knowledge, leads, and contributes to complex projects, and exercises independent judgment in resolving business issues and establishing policies
• Develops and builds productive internal/external working relationships and may provide mentoring and guidance to lower-level employees

Education & Experience Recommended
• Four-year or Graduate Degree in Mathematics, Statistics, Economics, Computer Science, or any other related discipline or commensurate work experience or demonstrated competence.
• Typically has 7-10 years of work experience, preferably in data analytics, database management, statistical analysis, or a related field.

Knowledge & Skills

• Analytics and problem solving: exploratory analysis, root-cause analysis, metric design, data validation, anomaly detection, and ability to diagnose complex data issues across multiple factors

• Data quality and governance: profiling, anomaly detection, metric validation, documentation, data lineage, privacy awareness, and the ability to communicate quality risks and remediation paths

• Business intelligence and visualization: experience with Power BI, Qlik, advanced Excel, or similar tools to build stakeholder-ready dashboards, analyses, and presentations

• Python for data analysis, validation, automation, time-series analysis, reproducible workflows, and tooling to support recurring quality checks and investigations

• SQL, including complex joins, CTEs, window functions, query performance optimization

• Databricks and modern analytics tooling: ability to work in notebooks, queries, dashboard-supporting datasets, and AI-assisted development environments while maintaining reproducible and reviewable outputs

• Forecasting and time-series: ability to support forecasting partners, interpret restatements and metric volatility, and contribute to forecasting automation or time-series analysis workflows

• Applied statistics: sampling, confidence intervals, and basic experiment/pre-post evaluation (role-dependent)

• Strong documentation habits for code and process development, data analyses and investigations, data lineage, and stakeholder guidance. Familiar with version control (e.g., Git), Jira, and Confluence

HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).

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