Marketing Measurement Data Sci...


HP’s growing Global Marketing Measurement and Optimization team is responsible for building and deepening a holistic view of HP’s marketing performance and making recommendations to improve it through the use of data and analytics.

We are looking for a world-class measurement science professional to join our team. You’ll lead the development of quantitative research, casual inference, and predictive models to understand and optimize the drivers of consumer behavior and marketing performance.

Key responsibilities:

  • Provide thought leadership in marketing analytics and technical innovation by working collaboratively with cross-functional teams to develop appropriate analytical models and identify incremental revenue margin/ productivity opportunities

Establish the methodological approaches to measuring multivariate drivers of marketing performance, funnel progression, conversion, abandonment, customer retention, consumer lifetime value.

  • Identify and optimize key drivers of marketing performance, user growth and engagement
  • Propose measurement methodologies for understanding business impacts for business process changes, KPIs and drive adoption across consumer-facing businesses
  • Build and deploy methodologies for the identification and tracking of (and response to) deviations in core KPIs
  • Provide senior leaders/owners actionable recommendations and strategic plan based on analytical research
  • Education

    • Bachelor Degree in economics, statistics, computer science, or similar field with quantitative focus
    • Advanced degree (Masters or PhD) in a related field preferred


    • 5+ years relevant professional work experience, with at least 3 years of relevant work experience in quantitative modeling.
    • Knowledgeable in market-mix modeling, ROI modeling, and modeling value and business cases. Experience with and ability to learn media & advertising viewing and measurement data and techniques. Understanding of TV and digital media spaces is a plus.
    • Experience using statistical techniques such as PCA, Factor analysis, ANCOVA, ARIMAX, Logistic regression, CHAID, etc.
    • Knowledge about trend analyses, Bayesian statistics, multivariate statistics, sampling, Linear Programing, Monte-Carlo simulations, bias reduction, indirect estimation, data aggregation techniques, automation, generalization.
    • Proficient in SQL, R, SAS, Python or other statistical packages.
    • Knowledge in Spark and/or Hadoop a plus.
    • Expertise in standard analysis and presentation software (Excel, PowerPoint).
    • Comfortable leading and mentoring junior analysts and data scientists to scale and extend own work
    • Excellent problem solving skills.

    To apply for this job please visit