Senior Data Analyst
On-siteChennai, Tamil Nadu, India
Job Summary
Analyse audience behaviour, segment performance, and supply-side inventory quality to inform targeting efficiency and buying decisions. Build forecasting models for impressions and pricing trends, while developing self-serve dashboards that surface actionable intelligence on bid win rates, auction efficiency, and pacing. Collaborate with engineering and ML teams to validate pipelines, interpret model outputs, and design experiments testing bidding strategies and supply path optimisations. Apply sampling techniques to efficiently process large-scale event-level datasets and conduct geo-based analysis at the zip code level. Proactively surface trends and growth opportunities to leadership with data-backed recommendations.
Required Qualifications
- Experience working with large-scale data platforms such as BigQuery, Snowflake, or Redshift — ideally with high-volume event-level or log-level data.
- Expert-level SQL proficiency for analysis, automation, and statistical work.
- Proficiency in data visualisation tools (Looker, Tableau, or Power BI) and the ability to design clear, intuitive dashboards tailored to different audiences —from traders and analysts to executive stakeholders.
- Strong analytical thinking with the ability to quickly ramp up on complex domain concepts — including auction mechanics, audience targeting, and supply-demand dynamics.
- Solid understanding of sampling techniques — including stratified, systematic, and cluster sampling — and the ability to apply them appropriately to large datasets to produce statistically sound and computationally efficient analyses.
- Demonstrated ability to collaborate with engineering teams — including experience with data pipeline validation, event instrumentation, and working within a modern data stack (dbt, Airflow, or similar).
- Comfort working alongside data science and ML teams — able to understand model concepts, interpret ML outputs, and bridge the gap between model development and business application without necessarily building models yourself.
- Solid grasp of visualisation principles: choosing the right chart types, avoiding misleading representations, and presenting data narratives that drive decisions rather than just display numbers.
- Experience with geo-based analysis, including working with zip code or sub-regional level datasets, spatial data tools, or geographic segmentation techniques.
- Strong ability to communicate complex findings to both technical teams and non-technical stakeholders.
- Experience designing and interpreting A/B tests and experiments with statistical rigour.
Desired Qualifications
- Prior experience in Ad Tech, programmatic advertising, or a DSP/SSP environment.
- Familiarity with DSP metrics (win rate, eCPM) and programmatic concepts (RTB, bid shading).
- Experience with supply path optimisation analysis or direct SSP/exchange integrations.
- Knowledge of audience segmentation, lookalike modelling, or data clean room technologies.
- Exposure to ML techniques applied to bid optimisation, audience scoring, and experience operationalising ML model outputs into reporting or business workflows.
- Experience with inventory forecasting methodologies or time-series analysis.
- Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, or any Engineering discipline.
- 6+ years in data analytics, ideally in a fast-paced, data-intensive environment
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