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Senior Digital Marketing Analyst

Posted about 1 month agoInactiveViewed

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💎 Seniority level: Senior, 3-5 years

📍 Location: United States

💸 Salary: 90000.0 - 110000.0 USD per year

🔍 Industry: B2B technology

🏢 Company: TechnologyAdvice👥 251-500E-CommerceLead GenerationSaaSB2BMulti-level Marketing

🗣️ Languages: English

⏳ Experience: 3-5 years

🪄 Skills: SQLData AnalysisMachine LearningGoogle AnalyticsTableauSEOData visualizationA/B testing

Requirements:
  • Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Marketing Analytics, or related field.
  • 3-5 years of experience with digital marketing platforms and concepts.
  • Experience with Google Analytics, Google Tag Manager, Facebook Ads Manager, Google Search Console, SEO, SEM, and social media analytics.
  • 2+ years of experience using BigQuery and SQL.
  • Experience with data visualization tools like Tableau or Looker/Google Data Studio.
  • Clear written and verbal communication skills.
  • Strong analytical thinking and problem-solving skills.
  • Knowledge of statistical techniques for data analysis.
  • Ability to work collaboratively in cross-functional teams.
  • Attention to detail and interest in industry trends and technologies.
  • Agile professional suited for a fast-paced environment.
  • Knowledge of machine learning and predictive modeling is a plus.
  • Knowledge using DOM in JavaScript is a plus.
Responsibilities:
  • Collect, extract, and integrate data from various digital marketing sources.
  • Work with APIs and data connectors for smooth data flow.
  • Connect and draw insights from multiple data sets.
  • Clean, preprocess, and transform raw data for accuracy.
  • Handle missing data and outliers effectively.
  • Perform exploratory data analysis for trends and insights.
  • Utilize statistical techniques for data relationships.
  • Build predictive models for campaign performance.
  • Analyze effectiveness of digital marketing campaigns.
  • Provide recommendations to optimize campaign performance.
  • Segment audiences based on demographics and behavior.
  • Analyze customer journey data for improvement touchpoints.
  • Support A/B testing and interpret results.
  • Create dashboards and reports with visualization tools.
  • Present data-driven insights to teams and management.
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