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Common mid-level analytics role, metro location, and broad skillset drive high applicant competition.
Core data analytics skills transfer across industries, though retail/CPG preference raises domain specificity.
No explicit years but multiple mandatory technical skills and statistical requirements increase filter strictness.
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Develop and implement statistical and machine learning models (regression, Bayesian) for business decision support in consumer and marketing analytics.
Handle diverse data sources (structured and unstructured) to create data models, reporting capabilities, and actionable insights using Python, R, SQL, and visualization tools like Power BI or Tableau.
Deliver insights and results through advanced analytics and visualization with ownership of tasks, working independently under tight deadlines.
Educational Qualification: Bachelor’s or Master’s degree, preferably in Statistics, Mathematics, Data Science, Computer Science, or Business Analytics.
Technical Skills: Proficient in Python, R, SQL, Power BI or Tableau, MS Excel, and MS PowerPoint.
Work Experience Required: Not explicitly mentioned in the JD.
Language Proficiency: English at a professional level (C2).
Strong expertise in statistical modeling and machine learning techniques applied to consumer and marketing data, with practical experience in retail, FMCG/CPG domains considered an advantage.
Hands-on experience working with large and diverse datasets including customer/shopper level data, capable of independent task management and proactivity.
Comfortable delivering complex analytical insights through visualization and clear communication to business stakeholders.