Sales Analyst

Qualifications

• Bachelors or advanced degree in a quantitative field for instance a Master s degree or PhD in data science or math (e.g., Computer Science, Mathematics, Statistics, Data Science) or equivalent experience
• 7 years + of relevant advanced analytics experience in Marketing or Commercial in either Retail, or CPG industries. Other B2C domains can be considered
• Proven experience with medium to large size data science projects
• Advanced knowledge of key data science techniques:
  • Combining data from multiple sources through APIs, Semantic Web, etc.
  • Data preparation and feature engineering
  • Supervised / Unsupervised learning
  • Collaborative Filtering
  • Location Analytics & Intelligence
• Proficiency in programming languages such as Python, R, or SQL.
• Good to have experience with data processing frameworks (e.g., Hadoop, Spark)
• Good to have understanding of data engineering principles, data integration, and ETL processes.
• Excellent problem-solving skills and the ability to translate business needs into data-driven solutions.
• Strong communication and interpersonal skills, with the ability to effectively convey complex concepts to both technical and non-technical stakeholders.

• Bachelors or advanced degree in a quantitative field for instance a Master s degree or PhD in data science or math (e.g., Computer Science, Mathematics, Statistics, Data Science) or equivalent experience
• 7 years + of relevant advanced analytics experience in Marketing or Commercial in either Retail, or CPG industries. Other B2C domains can be considered
• Proven experience with medium to large size data science projects
• Advanced knowledge of key data science techniques:
  • Combining data from multiple sources through APIs, Semantic Web, etc.
  • Data preparation and feature engineering
  • Supervised / Unsupervised learning
  • Collaborative Filtering
  • Location Analytics & Intelligence
• Proficiency in programming languages such as Python, R, or SQL.
• Good to have experience with data processing frameworks (e.g., Hadoop, Spark)
• Good to have understanding of data engineering principles, data integration, and ETL processes.
• Excellent problem-solving skills and the ability to translate business needs into data-driven solutions.
• Strong communication and interpersonal skills, with the ability to effectively convey complex concepts to both technical and non-technical stakeholders.