Analytics & Insights Manager (Marketing)

ADNOC Group; Abu Dhabi; On-site; AED 30,000 - 50,000; Full time

Job summary

A leading company is seeking an Analytics and Insights Manager to drive data analysis and insights for marketing programs. The role involves working with various teams to optimize campaign performance, develop strategic recommendations, and enhance customer engagement through advanced analytics.

Qualifications

• 6+ years of experience in data and analytics functions.
• Proficiency in data analytics tools.
• Experience with ML models.

Responsibilities

• Provide data-driven insights to enhance marketing effectiveness.
• Analyze marketing performance data across channels.
• Build and maintain marketing dashboards for real-time tracking.

Skills

Analytical skills

Strategic thinking

Communication

Interpersonal skills

Education

Bachelor's degree in Data Science, Business Administration, Statistics

MBA or equivalent advanced degree

Tools

SQL

Python

R

Google Analytics

Power BI

Job description

Role Overview:

The Analytics and Insights Manager (Marketing) will work with cross functional stakeholders across Loyalty, Marketing & Digital IT to provide deep data insights into the effectiveness of Marketing programs / campaigns. This covers performance of Marketing campaigns and associated customer behaviour. In addition, the role will also track/report performance across media channels and optimise the campaigns based on insights. The role will be essential in partnering with all the stakeholders to track effectiveness of Marketing programs and spends.

Key Responsibilities:

Analytics and Insights:

• Responsible for providing data-driven insights and strategic recommendations to enhance marketing effectiveness, customer engagement, and business growth by informing decision-making and optimize campaigns across all channels.
• Analyze marketing performance data across channels (e.g., digital, social media, email, and offline campaigns).
• Develop actionable insights to improve customer acquisition, retention, and engagement strategies.
• Monitor key performance indicators (KPIs) and report on campaign effectiveness & ROI
• Identify trends, opportunities, and risks through deep-dive analyses.
• Work with marketing teams to optimize campaigns based on data-driven insights.
• Leverage A/B testing, cohort analysis, and predictive modelling to enhance campaign outcomes.
• Build and maintain marketing dashboards for real-time tracking of performance metrics
• Utilize advanced analytics tools such as SQL, Python, R, Google Analytics, BI.
• Involved in ML models operationalization and business value realization.
• Support the development and adoption of predictive analytics, AI/ML models for mass marketing to: optimize test learn across initiatives, forecast customer behaviour, acquisition / conversion models to NFR, look alike models, MMM model etc.
• Communicate and present complex data and insights in a clear and compelling way to stakeholders, using data storytelling and visualization tools
  
  

Process and Policy Development:

• Support the development of RACI models to clearly define roles and responsibilities with Loyalty, Marketing, Retail, Digital (IT) and other stakeholders.
• Ensure integration of data analytics functions with overall business objectives.
  
  

Stakeholder Management:

• Collaborate with internal stakeholders, including retail business leads, IT, finance, and operations & external stakeholders such as advertising agencies, media agency, marketing analytics agency, consumer research etc
• Serve as the primary point of contact for internal stakeholders for C Store business analytics
  
  

Qualifications:

• Bachelor's degree in Data Science, Business Administration, Statistics, or a related field; MBA or equivalent advanced degree preferred.
• 6+ years of experience on data and analytics functions preferably in large B2C Marketing organisations or Advertising / Media Agencies
• Strong strategic thinking, analytical, and problem-solving skills.
• Good communication and interpersonal skills.
• Ability to thrive in a dynamic and fast-paced environment.
  
  

Technical Skills

• Proficiency in data analytics tools and software (e.g., SQL, Dataiku Python, R, Tableau, Power BI).
• Experience with data infrastructure and cloud platforms (e.g., AWS, Azure, Google Cloud).
• Knowledge of statistical analysis, machine learning, and data visualization techniques.
• Experience in ML models operationalisation and business value realisation
• Familiarity with data privacy regulations and best practices.
  
  

Professional Skills:

• Ability to manage multiple projects simultaneously.
• Expertise in data analysis, and business intelligence.
• Ability to develop and implement data strategies and roadmaps.
  
  

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