Detalii loc de munca - București si altele
Descrierea jobului - Cluj Napoca si altele
Do you have at least three to five years experience in marketing analytics and one year experience building marketing mix models? Do you have experience using software to solve problems with large data sets? Do you have a bachelors or masters degree in Statistics, Economics or some other quantitative degree from a reputable university program? This job may be for you. Job Description: Ignite Technologies is expanding our professional services team to build marketing mix models and digital attribution solutions for our Blue Chip roster of clients. This is a great opportunity to build your experience working with world class marketing teams and helping them achieve 100% Customer Success. Company Description: Ignite Technologies helps customers ignite the power of their workforce to ignite better business performance through the deployment of best-in-class business applications and application development platforms across a range of functional domains. Ignite’s mission is to develop and deliver an expanding set of unique business applications that help organizations perform better by enhancing the capabilities and impact of their workforce. Total compensation: $50,000/year Location: Global (remote) 40 hours per week Key Responsibilities: A Marketing Analytics Manager manages data integration, data analysis, model building, and contributes to the development of recommendations for multiple customers. This is a customer-facing role; analysts attend and facilitate key meetings and will (after initial onboarding) manage some customer-facing activities independently. Responsibilities Include: Drive the development of budget-level marketing mix optimization and digital attribution models that create insightful recommendations. Must understand the customer’s business and decision making process. Craft stories and develop presentations that provide relevant insights and clear recommendations to customers. Present findings to customers. Work with agencies and customer to collect, analyze and interpret source data. Lead the data integration process. Understand and apply both aggregated and disaggregated marketing data to building analytic models. Aggregate data sources include media, promotional and trade plans, econometric data and exogenous factors that drive customer sales. Dis-Aggregate data include impressions, clicks and conversions. Build marketing models and provide analysis to meet customer needs in a timely manner, with some direction and guidance from Director.
Required Skills and Expertise: Curiosity, especially about media, advertising, and consumer behavior Empathy Interest in helping others succeed Strong understanding of digital advertising and related measurement systems Ability to select appropriate, intuitive ways of visualizing data based on business need Attention to detail sufficient to work with large datasets while minimizing error and rework Ability to deliver against established client timelines, often balancing multiple client needs at once Ability to operate with a good mix of independence and collaboration, seeking guidance when appropriate Required Education and Experience: Bachelor’s degree required Concentration in business, statistics, mathematics, economics, or another quantitative field may be helpful in this role, but not required 3-5 years of experience in marketing consulting or analytics with at least one year of marketing mix modeling or digital attribution experience that includes one or more of the following elements: Creating or driving action with digital attribution analyses, familiarity with attribution and vendor tools a plus. (GA/Adometry, Convertro, VisualIQ, Rakuten, Facebook, Twitter, Pinterest analytics) Developing dashboards using business intelligence tools. (Tableau, Qlik, YellowFin) Managing, assessing, transforming large data sets (here, “large” means any dataset big enough that visual inspection is not effective and queries are required to check or transform it – this could include Hadoop- or Spark-scaled big data sets, or larger datasets in SQL, R, SAS or similar)