Data Analyst
Posted just now INR 800,000 - 1,000,000 / year
Role Overview
As a Data Analyst, you turn campaign, bidding, and audience data into decisions. The role today is as much about judgment as it is about querying: our analysts work on top of a modern cloud data stack and alongside internal AI systems: defining the metrics that matter, validating what automated tools and agents produce, and making sure the numbers that reach stakeholders are trustworthy. You will partner with product, engineering, and data science to improve both our advertising outcomes and the analytics platform itself.
Key Responsibilities
As a Data Analyst, you turn campaign, bidding, and audience data into decisions. The role today is as much about judgment as it is about querying: our analysts work on top of a modern cloud data stack and alongside internal AI systems: defining the metrics that matter, validating what automated tools and agents produce, and making sure the numbers that reach stakeholders are trustworthy. You will partner with product, engineering, and data science to improve both our advertising outcomes and the analytics platform itself.
Key Responsibilities
- Analyze at scale. Explore large campaign, bidding, and audience datasets in our cloud warehouse (Snowflake, Athena) to surface trends, anomalies, and optimization opportunities across political, healthcare, and BFSI campaigns.
- Own metric definitions. Help define and maintain the KPIs and semantic definitions behind self-serve and natural-language analytics, so that a question asked in plain language returns an answer you'd stake your name on.
- Validate AI-assisted output. Use AI copilots and internal diagnostic agents to accelerate analysis, and apply the judgment to catch where automated SQL, summaries, or recommendations are wrong before they influence a decision.
- Build and maintain reporting. Develop dashboards and visualizations (Data Studio, Tableau, or PowerBI) that track performance and communicate findings clearly to technical and non-technical audiences.
- Run ad-hoc analysis. Translate open-ended business questions into rigorous analyses, separate signals from noise, and quantify the impact of your recommendations.
- Collaborate cross-functionally. Work with product and engineering to ship data-driven optimizations, and feed real analyst pain points back into platform improvements.
- Uphold data privacy and compliance. Handle sensitive political and healthcare data responsibly, in line with the regulatory expectations of those verticals.
- Stay current. Track developments in analytics, AI tooling, and ad-tech, and bring the useful ones into how the team works.
- Bachelor's degree or higher in a quantitative field: Mathematics, Statistics, Economics, Computer Science, Engineering, or related.
- Strong SQL, with hands-on experience querying a cloud data warehouse (Snowflake, Athena preferred).
- Proficiency in Python (or R) for data manipulation and analysis (e.g., pandas).
- Hands-on experience with at least one BI/visualization tool: Data Studio, Tableau, or PowerBI.
- Solid statistical literacy: comfort with distributions, cohorts, hypothesis testing, and reading experiment results.
- Comfort using AI/LLM copilots in day-to-day analysis, plus the critical thinking to recognize and correct when they're wrong.
- Excellent communication: able to present complex findings clearly to both technical and non-technical stakeholders.
- Detail-oriented, curious, and driven to get to the real answer rather than the convenient one.
- Exposure to programmatic advertising / ad-tech: RTB, DSPs, audience or identity data.
- Experience working alongside AI agents or natural-language / semantic analytics layers (e.g., validating agent-generated queries and answers).
- An evaluation mindset: designing checks that tell you whether an automated or AI-generated output is actually correct.
- Familiarity with analytics-engineering basics (e.g., version control, modular data models).
- Awareness of privacy and compliance considerations in political advertising and healthcare data handling.
- Prior internships or projects in data analysis, marketing analytics, or ad-tech (a plus, not a requirement).
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