About the role
The ideal candidate must possess a strong analytical mindset, domain awareness, and communication skills, with the ability to interpret complex data into actionable business insights. They should demonstrate ownership in reporting, ad-hoc analysis, and performance diagnostics, while collaborating with cross-functional teams to shape data-driven decision-making.
Role and Responsibilities:
• We are looking for candidates with strong analytical thinking, business acumen, and experience in turning data into actionable insights to support both day-to-day operations and strategic decisions.
• Strong hands on knowledge of marketing, Sales and Revenue analytics and marketing frameworks.
• Experience with GCP, Adobe Analytics, Salesforce CRM systems, and marketing automation platforms.
• Conduct deep-dive analyses to identify performance trends, diagnose drivers, and uncover opportunities for process or strategy optimization.
• Frame and test data-driven hypotheses, define KPIs and metrics to assess outcomes.
• Collaborate with stakeholders across business, product, and marketing teams to define analytics requirements and translate them into structured analysis.
• Proficient in visualization using Looker with hands on SQL.
• Lead regular and ad-hoc reporting and insight generation to support business-as-usual (BAU) activities.
• Provide actionable recommendations based on data trends, statistical analyses, and visualizations.
• Support design of experimentation frameworks and testing methodologies (e.g., A/B testing, pre-post analysis).
• Document analytical approaches and ensure consistency and accuracy in data interpretation.
• Attribution Model Maintenance & Optimization: Maintain a pre-defined marketing attribution framework that aligns with corporate goals and integrates seamlessly with existing data infrastructure
Technical and Functional Skills:
• BE/B.Tech or Bachelor’s degree in Mathematics, Statistics, Economics, Computer Science or related field with 1+ years of experience in data analytics or business intelligence.
• Strong proficiency in SQL for data querying and transformation.
• Experience in data visualization and dashboarding using Looker, , or equivalent tools.
• Hands-on with Excel, and familiarity with scripting languages like Python or R (good to have).
• Solid understanding of statistical techniques and their applications in experimentation and optimization (e.g., A/B testing, regression analysis).
• Ability to independently explore data, structure analytical approaches, and present compelling narratives from data insights.
• Strong knowledge of marketing analytics and marketing frameworks.
• Able to analyze and conduct impacting driver analysis.
• Exposure to tools like Google Analytics.
• Strong business acumen and the ability to translate data into meaningful recommendations for business teams.