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    Data Scientist, Marketing Analytics - San Jose, United States - McAfee

    McAfee
    McAfee San Jose, United States

    4 weeks ago

    Default job background
    Full time
    Description


    Role Overview:

    McAfee's Marketing Data Science team is looking for their next Data Scientist The role is centered on using quantitative skills, statistical methodologies, programming skills and business judgement to convert analytic findings into customer insights that can be used to accelerate marketing initiatives. You will play a key role in adding nuance and sophistication to McAfee's ability to evaluate and optimize portfolio spend with respect to acquiring Direct-to-Consumer subscribers.

    You will use your experience and domain-expertise to help develop, implement and iterate on models and analysis that help optimize existing initiatives and identify new opportunities for driving ROAS and subscriber-LTV. You will also leverage your programming and visualization-skills, data-acumen and business-domain-knowledge to create powerful insights and distill/ present findings and recommendations to a varied audiences ranging from other data-scientists to senior executives.

    This is a role based out of the United States or Canada and we are only considering candidates based out of the United States or Canada at this time. We are not offering relocation at this time.


    Job Description:

    About the role:

    • You will apply your knowledge of the digital marketing domain to inform, iterate and improve upon Marketing-Mix-Models with the goal of optimizing and accurately forecasting ROAS with a deep understanding of topics such as:

    Time-decay and relationship to ROAS for specific channels

    Panel/mixed-effects modeling

    Markov-chain analysis

    ROAS/marginal-ROAS optimization

    'what-if?"/scenario analysis

    • You will use predictive modeling, statistics, Machine Learning, Data Mining, and other data analysis techniques to collect, explore, and extract insights from structured and unstructured data
    • You will apply data-wrangling / data-engineering skills towards development of ETL pipelines to support both modeling-efforts and creation/consolidation of analytical datasets stitched together from a variety of sources and platforms
    • You will employ your domain-knowledge and insights with respect to CAC and ROAS to enhance existing framework for computing customer-LTV and the associated CAC (customer acquisition cost)
    • Redefine most relevant groupings for LTV projection and forecasting through ML/statistical methods to create more accurate LTV projections and insights
    • You will identify driver and leading indicators relevant to both LTV and CAC computations to help develop a 'predictive view' of LTV trajectory

    About you:

    • You have 5 years of experience in a data-science role and a Master's in Statistics, Data Science, Computer Science, Econometrics or other quantitative fields is heavily preferred
    • You have at least 3 years of experience working daily with either Python or R for data-collection, ingestion and analysis.
    • You have at least 3 years of experience in applied predictive/ML modeling using either R or python (python preferred)
    • You have a strong understanding of Market-Mix-Modeling and Multi-Touch-Attribution frameworks with the demonstrated ability to iterate, enhance, scale and improve accuracy and reliability of insights You have at least 3 years of experience with building and refining time-series forecasts including application of hierarchical and grouped methodologies
    • You have familiarity with NLP techniques including Transformer Models
    • You have advanced SQL skills including the ability to query structured/semi-structured data from an analytical perspective and scope and implement ETL pipelines
    • You can own data science projects of varying scope from concept to delivery while focusing on delivering a solution to address the original problem statement to achieve success


    #LI-Remote

    Accommodations:

    McAfee recognizes and supports its obligation to reasonably accommodate applicants and employees with disabilities. We are here to help. Please let us know if you need a reasonable accommodation for any part of the application, interviewing, hiring, or at any other time during the employment process. Please do not include personal medical information in the email.

    Diversity is foundational for our business success. We want to be a workplace of choice for all people and we value the unique perspectives offered by a diverse workforce. McAfee does not unlawfully discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, citizenship, disability, protected veteran status, age, ancestry, medical condition, genetic information, marital status, pregnancy, or any other legally protected status. This principle applies to all areas of employment: recruitment and hiring, training, performance evaluations, promotions and transfers, compensation and benefits, and social and recreational programs.

    McAfee desires to be an employer of choice with an inclusive environment for all individuals. As part of this goal and in compliance with various laws and regulations, McAfee provides reasonable accommodation to applicants and employees. Requests for reasonable accommodation for applicants and employees are evaluated on a case-by-case basis.

    Posting Statement:

    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.

    The starting pay range for this position is $107,430.00-$176, McAfee takes into consideration an individual's skillset, experience and location in making final salary determinations. For further details, please discuss with the Talent Acquisition Partner.
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