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Senior Data Scientist, Forecasting and Analytics

Part-time

McAfee, Inc.

San Jose, CAHybridPart-time$107–176K/yrTracked 1w agoSeen in employer's feed 3 days ago

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At a glance

Compensation
$107–176K/yr
Location
San Jose, CAHybrid
Schedule
Part-time
Work Authorization
Not specified

Requirements

Credentials this posting asks for.

Master's degree

Job overview

McAfee, Inc. is hiring a Senior Data Scientist, Forecasting and Analytics. McAfee seeks a technically strong, business‑oriented Senior Data Scientist to own forecasting and planning initiatives, turning complex data into actionable insights that improve acquisition, retention, customer experience, and business planning value.

Key focus areas include Own forecasting models for key marketing and business outcomes, Support planning cycles by translating trends and seasonality into forecasts, and Develop planning tools, models, and readouts for stakeholder decision making.

Important skills include Forecasting, Machine Learning Forecasting, Translating Analytical Findings, Work Independently, Frame Ambiguous Problems, and Build Reliable Models. Preferred (not required): Journey Analytics, Subscription Analytics, Ecommerce, and SaaS.

Skills & qualifications

RequiredNice to have

Skills

ForecastingMachine Learning ForecastingTranslating Analytical FindingsWork IndependentlyFrame Ambiguous ProblemsBuild Reliable ModelsInfluence Decisions Through Data-Driven StorytellingPythonSQLCommon Data Science LibrariesStatistical Modeling LibrariesTime-Series AnalysisSeasonalityTrend AnalysisLag EffectsScenario PlanningModel BacktestingMarketing AnalyticsCustomer AnalyticsCampaign Performance AnalysisAcquisition AnalysisRetention AnalysisConversion AnalysisLifetime Value AnalysisTranslate Ambiguous Business QuestionsInfluence Marketing and Business StakeholdersJourney AnalyticsSubscription AnalyticsEcommerceSaaSConsumer Digital BusinessesA/B TestingCausal InferenceUplift ModelingSurvival AnalysisBayesian ModelingPersonalization MethodsWorking With Large-Scale Customer DatasetsWorking With Behavioral DatasetsWorking With Clickstream DatasetsWorking With Campaign DatasetsWorking With Planning DatasetsWorking With Transaction-Level DatasetsDatabricksSnowflakeBigQueryCreating Executive-Ready Presentations

Qualifications

7+ Years Data Science Experience7+ Years Machine Learning Experience7+ Years Forecasting Experience7+ Years Advanced Analytics ExperienceMaster’s Degree in a Quantitative DisciplinePhD in a Quantitative Discipline

Benefits

Medical Insurance
Dental Insurance
Vision Insurance
401(k) Match
Parental Leave
Paid Time Off

Full job description

Role Summary

We are seeking a technically strong and business-oriented Senior Data Scientist to own our forecasting and planning initiatives. With a focus on forecasting as it relates to planning and marketing analytics; this role will turn complex data into actionable insights that improve acquisition, retention, customer experience and business planning value.

The ideal candidate is highly proficient in time series and machine learning forecasting methods and equally strong at translating analytical findings into clear, engaging recommendations for business stakeholders and executives. This person should be able to work independently, frame ambiguous problems, build reliable models, and influence decisions through data-driven storytelling.

This is a hybrid role located within one of our hub locations i.e. Dallas, TX, New York, NY, San Jose, CA or Newport Beach, CA. Your will be required to come into an office on an as needed basis and work from your home office the rest of the time.

Position Details

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.

#LI-Hybrid

Company Overview

McAfee is a leader in personal security for consumers. Focused on protecting people, not just devices, McAfee consumer solutions adapt to users’ needs in an always online world, empowering them to live securely through integrated, intuitive solutions that protects their families and communities with the right security at the right moment.

Company Benefits and Perks

We work hard to embrace diversity and inclusion and encourage everyone at McAfee to bring their authentic selves to work every day. We offer a variety of social programs, flexible work hours and family-friendly benefits to all of our employees.:

  • Bonus Program

  • 401k Retirement

  • Medical, Dental, Vision, Basic Life, Short Term Disability and Long-Term Disability Coverage

  • Paid Parental Leave

  • Support and Community Involvement

  • 14 Paid Company Holidays

  • Unlimited Paid Time Off for Exempt Employees

  • 96 Hours of Sick Time and 120 Hours of Vacation for Non-Exempt Employees Accrued Each Year

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

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