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About the role:
Forecasting & Planning
Ownership and maintenance of forecasting models for key marketing and business outcomes, including revenue, demand, conversion, retention, and customer value.
Support planning cycles by translating historical trends, seasonality, campaign activity, customer behavior, macro factors, and business assumptions into clear forecasts and scenarios.
Develop planning tools, models, and readouts that help stakeholders and executives understand expected performance, pacing, and business tradeoffs.
Monitor forecast accuracy, diagnose variance versus plan, and recommend adjustments based on changing business conditions.
Advanced Analytics & Machine Learning
Develop and validate data science models that support customer behavior analysis, segmentation, propensity modeling, churn/retention analysis, personalization, and lifetime value.
Build analytical frameworks that help stakeholders understand customer needs, behavior drivers, performance trends, and areas for improvement.
Marketing Insights & Stakeholder Storytelling
Partner with Marketing, Finance, Product, Analytics, and Data Engineering teams to define business questions, analytical approaches, data requirements, and success metrics.
Translate complex model outputs into clear recommendations that help stakeholders understand what happened, why it happened, and what actions to take.
Communicate insights through compelling presentations, dashboards, and executive-ready readouts tailored to executive and other potentially non-technical audiences.
Proactively identify insights, risks, and opportunities in the data rather than waiting for narrowly defined requests.
About you:
7+ yrs experience applying data science, machine learning, forecasting and/or other advanced analytics in a business environment.
Strong proficiency in Python, SQL, and common data science or statistical modeling libraries.
Strong working knowledge of time-series analysis, forecasting, seasonality, trend, lag effects, scenario planning, and model backtesting.
Experience with marketing analytics, customer analytics, campaign performance, acquisition, retention, conversion, or lifetime value analysis.
Ability to translate ambiguous business questions into structured analytical plans and actionable recommendations.
Strong communication and data storytelling skills, with the ability to influence marketing and business stakeholders.
Preferred Qualifications
Master’s degree or PhD in a quantitative discipline.
Experience with customer lifecycle analytics, journey analytics, subscription analytics, ecommerce, SaaS, or consumer digital businesses.
Familiarity with experimentation, causal inference, uplift modeling, survival analysis, Bayesian modeling, or personalization methods.
Experience working with large-scale customer, behavioral, clickstream, campaign, planning, or transaction-level datasets.
Experience using cloud data platforms such as Databricks, Snowflake, BigQuery, or similar environments.
Experience creating executive-ready presentations that connect analytical findings to business strategy and operational decisions.
We're serious about our commitment to diversity which is why McAfee prohibits discrimination based on race, color, religion, gender, national origin, age, disability, veteran status, marital status, pregnancy, gender expression or identity, sexual orientation or any other legally protected status. Pay Range: The anticipated compensation for this position is USD $107,430.00/Yr. - USD $176,490.00/Yr. depending on experience and qualifications. Job Applicant Privacy Notice: Please click here to view and download the Job Applicant Privacy Notice, which applies to all McAfee job applicants who are residents of the state of California.
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