Description -

Job Summary

HP is seeking an experienced Performance Marketing Analytics Lead who is passionate about optimizing business outcomes at the intersection of dataanalytics, AI, and experimentation. This role sits within HP's eCommerce & Digital Marketing Analytics organization and plays a critical part in shaping how marketing investments are planned, tested, optimized, and scaled globally.

Using advanced analytics, media mix modeling (MMM), experimentation, machine learning, and AI‑enabled decisioning, this role drives quarterly, monthly, weekly, and in‑period marketing investment decisions across digital channels (including SEM, CSE, Affiliate, Display, Social, Email, and Partner channels). The role partners closely with marketing, data science, product, and engineering leadership to build scalable experimentation and optimization capabilities that improve acquisition, retention, lifetime value, margin, and overall marketing ROI.

This position applies deep subject matter expertise to complex problems, frequently contributes new ideas and methodologies, and may directly or indirectly lead analysts and data scientists while providing functional leadership within the marketing analytics domain.

Key Responsibilities

Performance Marketing & Optimization Leadership

• Lead digital marketing planning, optimization, and experimentation activities across the optimization process and cadence.
• Drive material improvements in acquisition, retention, and customer lifetime value through data‑driven optimization and experimentation.
• Own and evolve media mix planning tools, attribution frameworks, and optimization models used for scenario planning and investment trade‑offs.
• Perform regular intra‑month and in‑period optimization analyses, partnering with channel managers to deploy actionable recommendations.

Experimentation & Attribution

• Design, implement, and analyze adaptive test‑and‑learn programs (A/B, multivariate, quasi‑experimental designs) across demand generation channels.
• Evolve marketing attribution through experimentation, including multi‑touch, ML‑based, and incrementality‑driven approaches.
• Advise campaign optimization decisions through insights derived from attribution, experimentation, and causal analysis.
• Build reusable experimentation frameworks, methods, and standards to improve efficiency and consistency across analytics initiatives.

AI & Advanced Analytics Applications

• Apply advanced statistical methods and machine learning to optimize marketing performance, including:
  • Incrementality and causal inference
  • Media response and saturation modeling
  • Margin‑based and bid‑to‑profit optimization
  • Predictive modeling for efficiency, conversion, and value
  • Automated performance monitoring and anomaly detection
• Lead adoption of AI‑assisted and GenAI‑enabled analytics, such as:
  • AI‑generated insights, summaries, and decision narratives
  • Self‑service and prompt‑based analytical exploration
  • Automated interpretation of experimental results at scale
• Ensure analytical outputs are explainable, auditable, and aligned with business decision‑making.

Tools, Platforms & Enablement

• Build and evolve tools that enable evaluation and interpretation of experimental and marketing data at scale, including 1st‑party, platform, and agency data.
• Partner with product managers and data scientists to define the technical roadmap and vision for experimentation, measurement, and optimization.
• Advise leadership on key technical considerations tied to the marketing technology stack, data platforms, and AI readiness.
• Debug and resolve analytics and production issues across multiple marketing channels.

Cross‑Functional Influence & Strategy

• Partner with marketing leaders to develop a comprehensive understanding of investment opportunities and trade‑offs, translating insights into clear requirements and recommendations.
• Recommend go‑to‑market actions and optimization strategies to senior leaders based on analytical findings.
• Represent marketing analytics expertise to internal stakeholders and, as needed, external partners and vendors.
• Participate in defining and refining marketing and sales policies for specific product lines or regions in compliance with local regulations.

Leadership & Mentorship

• Lead or provide expertise to cross‑functional project teams.
• Provide mentorship, guidance, and training to junior analysts and data scientists.
• Act as a functional expert advising on process improvements, analytics standards, and best practices.
• Exercise significant independent judgment within broadly defined policies to achieve business objectives.

Knowledge & Skills

Marketing & Analytics Expertise

• Advanced understanding of marketing attribution, including multi‑touch, probabilistic, and ML‑based approaches.
• Proven success optimizing campaigns across paid and unpaid channels (SEO, SEM, CSE, Affiliate, Social, Email, Display, Partner).
• Expert knowledge of experimental design, causal inference, and statistical analysis.
• Strong grasp of eCommerce economics, digital marketing metrics, and performance drivers.

AI & Data Science

• Advanced experience with statistics, mathematics, and algorithmic modeling.
• Machine learning for prediction, optimization, and decision support.
• Experience working with structured and unstructured datasets.
• Familiarity applying GenAI / LLMs to analytics enablement and insight acceleration.

Technical & Platform Skills

• SQL, Python, R, SAS, or similar analytical languages.
• Data modeling, ETL/ELT, and modern data transformation techniques.
• BI, data visualization, and storytelling tools (e.g., Tableau, Power BI).
• Working knowledge of MarTech stacks, MRM, CRM, and CKM platforms.
• Ability to clearly communicate data product architectures and algorithm design to senior audiences.

Ways of Working

• Agile and project‑based delivery experience.
• Strong communication, storytelling, and executive presence.
• Proven ability to make informed trade‑offs under uncertainty.
• Self‑starter with strong execution discipline and deadline management.

Education & Experience

• Bachelor's, Master's, or PhD in Mathematics, Economics, Physics, Computer Science, Data Science, Marketing, or related field.
• 7-10+ years of experience in marketing analytics, data science, or digital optimization roles.
• 3+ years of hands‑on experience in experimentation design, causal analysis, or advanced statistical modeling at scale.
• Experience in digital media, MarTech, subscription, or technology‑driven businesses strongly preferred.

Impact & Scope

• Leads complex, high‑impact initiatives influencing global marketing investment decisions.
• Regular interaction with senior ICs, managers, directors, and executive leadership.
• Shapes how AI, experimentation, and analytics are operationalized across HP's digital direct marketing ecosystem.

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Equal Opportunity Employer (EEO) -

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).

Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence.

For more information, review HP'sEEO Policy or read about your rights as an applicant under the law here: "Know Your Rights: Workplace Discrimination is Illegal"