Senior Manager, Marketing Data Science, Predictive Marketing Tech...
Karkidi - Long Island City, New York, United States, 11101![Karkidi](/api/image?src=https%3A%2F%2Fgeneral-board-default.s3.us-east-2.amazonaws.com%2Fpublic%2Fimages%2Fdesk-360x180.webp&w=640&q=75&f=webp)
Work at Karkidi
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Overview
Is this the role you are looking for If so read on for more details, and make sure to apply today.You Will: Responsibilities:Predictive Modeling & Advanced Analytics: Build predictive models to predict customer behavior, such as churn, lifetime value, price sensitivity, channel preference and purchase propensity within the subscriptions businesses. Develop predictive models for upsell/cross sell across the different product lines.Media Spend Forecasting & Scenario Planning: Build predictive models to capture the effectiveness of marketing spend across channels and customer types; structure data integration, harmonization, and attribution processes in order to support robust modeling; build optimization tools to analyze and manage models holistically; socialize models with stakeholder teams; propose and explain marketing strategies that improve business outcomes and support stakeholders.Data-driven Marketing Strategies: Utilize advanced analytics and predictive techniques to analyze large volumes of customer data, including demographic information, transactional data, online behavior, and social media data. Derive actionable insights to optimize marketing strategies, improve customer targeting, and personalize marketing campaigns.Stakeholder Collaboration: Work closely with cross-functional teams, including marketing, sales, product, and finance, to understand their business needs and translate them into data-driven solutions. Present insights and recommendations to senior executives and stakeholders in a clear and compelling manner.You Have:
10+ years experience in Data Science, strategy, data, marketing, and/or general management preferred.Degree in a quantitative field such as Data Science, Statistics, Mathematics, or related disciplines.Experience in marketing analytics, data science, or a related field. Experience of media pricing analytics strategy with a focus on subscriptions is a plus.Proven expertise in predictive modeling, machine learning, data mining, and forecasting.Proficiency in programming languages such as Python, R, or SQL; experience working with large-scale databases and data manipulation.Understanding of marketing principles, customer segmentation strategies, and digital marketing channels.Strong business acumen and the ability to effectively communicate complex concepts to non-technical stakeholders.Experience with data visualization and reporting tools, such as Tableau or Power BI.Familiarity with marketing automation platforms, CRM systems, and digital analytics tools is a plus.Our Benefits:
Comprehensive Healthcare PlansPaid Time OffRetirement PlansComprehensive Insurance PlansLifestyle programs & Wellness ResourcesEducation BenefitsFamily Care Benefits & Caregiving SupportCommuter Transit ProgramSubscription DiscountsEmployee Referral ProgramLearn more about all our US benefits.All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, protected veteran status, or disability status. EEO/AA/M/F/Disabled/Vets.Dow Jones is committed to providing reasonable accommodation for qualified individuals with disabilities, in our job application and/or interview process. If you need assistance or accommodation in completing your application, due to a disability, please reach out to us at TalentResourceTeam@dowjones.com. Please put Reasonable Accommodation in the subject line. This inbox will not be monitored for application status updates.Business Area: Dow Jones - CMO - MarketingJob Category: Data Analytics/Warehousing & Business IntelligenceUnion Status: Non-Union rolePay Range: $135,000 - $165,000We recognize that attracting the best talent is key to our strategy and success as a company. As a result, we aim for flexibility in structuring competitive compensation offers to ensure we are able to attract the best candidates. The quoted salary range represents our good faith estimate as to what our ideal candidates are likely to expect, and we tailor our offers within the range based on the selected candidate's experience, industry knowledge, location, technical and communication skills, and other factors that may prove relevant during the interview process.
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