Senior Director Analytics (CPG & Retail)

Job Description

Skills:
Data Strategy Development, Advanced Statistical Analysis, Machine Learning Techniques, Data Visualization Tools, SQL and Database Management, Python or R Programming, Big Data Technologies, Stakeholder Management,

Our client, Global Data & Analytics firm is looking for Senior Director for the CPG Analytics Practice.

The Senior Director of Analytics will lead the analytics function, leveraging extensive experience to drive data-driven decision-making and business insights. This role is responsible for shaping the analytics vision and leading a high-performing team for CPG and Retail division. The ideal candidate will possess strong data engineering skills to complement their analytics expertise within the retail/CPG industry.

Key Responsibilities

  • Leadership and Strategy
  • Data Management and Governance
  • Advanced Analytics and Insights
  • Data Engineering and Infrastructure
  • Collaboration and Stakeholder Management
  • Project and Performance Management
  • Industry Leadership and Innovation

Experience

18+ years of experience in analytics, data science, data engineering, or a related field

7+ years of experience in a senior leadership role managing large analytics and data engineering teams.

Proven track record of driving significant business impact through advanced analytics and robust data infrastructure.

Technical Skills

Expertise in statistical analysis tools (e.g., R, SAS, SPSS) and data visualization tools (e.g., Tableau, Power BI).

Strong knowledge of big data technologies (e.g., Hadoop, Spark) and database management systems (e.g., SQL, NoSQL).

Proficiency in machine learning, predictive modeling, and other advanced analytics techniques. Extensive experience with data engineering tools and technologies, including ETL frameworks, data warehousing solutions, and cloud-based data platforms (e.g., AWS, Azure, GCP).

Strong programming skills in languages such as Python, Java, or Scala for data processing and analysis.

Experience with real-time data processing and streaming technologies (e.g., Kafka, Flink).