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Senior Data Analyst

Chennai, Tamil Nadu, India

TEGNA Inc. helps people thrive in their local communities by providing the trusted local news and services that matter most. With 64 television stations in 51 U.S. markets, TEGNA reaches more than 100 million people monthly across web, mobile apps, streaming, and linear television, while also maintaining a strong global presence in India with offices in Bangalore and Chennai that support technology, product, and business operations initiatives. Together, we are building a sustainable future for local news.

Position Overview

TEGNA is looking for a Senior Data Analyst is seeking a skilled and forward-thinking CloudEngineer to join our growing technology team. We are a demand-side platform (DSP) helping advertisers and agencies programmatically reach their target audiences at scale. We are looking for a Senior Data Analyst to drive insights across advertiser performance, audience quality, and supply-side partnerships — going beyond surface-level reporting to uncover the stories that data tells. In this role, you will work at the intersection of data, engineering, and data science — collaborating closely with our engineering team to maintain data integrity and with our ML team to translate model outputs into business intelligence.

You will analyse how audiences behave across our platform, evaluate the quality and efficiency of inventory sources, develop forecasts that help advertisers and internal teams plan with confidence, and surface actionable intelligence that helps our advertisers deliver better outcomes while growing the overall business.

What You’ll Do

 Analyse audience behaviour and segment performance to help advertisers improve targeting efficiency, reach, and campaign ROI across programmatic channels.

 Evaluate supply-side inventory quality — assessing publisher segments, bid stream data, win rates, and CPM trends — to inform smarter buying decisions and supply curation strategies.

 Build and own reporting on key DSP metrics: bid win rate, auction efficiency, costper outcome, audience match rates, and pacing performance.

 Develop and maintain inventory forecasting models to predict available impressions, audience reach, and pricing trends across supply segments —enabling better planning for advertisers   and internal teams.

 Conduct geo-based analysis at the zip code level to uncover regional audience patterns, inventory availability, and performance variations — supporting hyper-local targeting strategies and geo-specific advertiser campaigns.

 Apply sampling techniques to efficiently analyse large-scale bid-stream and event-level datasets, ensuring statistically representative insights without compromising on speed or infrastructure costs.

 Collaborate closely with the engineering team to define data instrumentation requirements, validate pipelines, and ensure the accuracy and completeness of data flowing into analytics systems.

 Partner with the data science and ML team to interpret model outputs — such as bid price predictions, audience scores, and churn models — and translate them into actionable business  insights and performance narratives.

 Work with tech success and engineering teams to diagnose campaign performance issues and identify optimisation opportunities across targeting, bidding, and creative.

 Develop self-serve dashboards and analytics tools that give internal teams and advertisers visibility into audience and supply performance.

 Design and evaluate experiments to test bidding strategies, audience models, and supply path optimisations — in close coordination with the ML team to ensure rigorous measurement of model-driven changes.

 Monitor and analyse data from DSP integrations with SSPs, DMPs, and data partners to assess signal quality and identify gaps, flagging data quality issues to engineering as needed.

 Proactively surface trends, anomalies, and growth opportunities to leadership with clear, data-backed recommendations.

 Apply best practices in data quality, experimentation, and reporting.

What you bring

 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.

Preferred Qualification

 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

Why TEGNA?

At TEGNA, we’re not just building systems, we’re redefining the media industry through technology. You'll join a team committed to transparency, shared understanding, and building high-impact platforms with speed and stability. As a DevOps Engineer, you’ll be at the heart of enabling our engineering teams to deliver at scale. Join us to shape the infrastructure behind great digital experiences and drive meaningful impact for millions of users!

EEO Statement:

TEGNA Inc. is a proud equal opportunity employer. We are proud to be an equal opportunity employer, hiring and developing individuals from diverse backgrounds and experiences to add to our collaborative culture. We value and consider applications from all qualified candidates without regard to actual or perceived race, color, religion, national origin, sex, gender, age, marital status, personal appearance, sexual orientation, gender identity or expression, family responsibilities, disability, medical condition, enrollment in college or vocational school, political affiliation, military or veteran status, citizenship status, genetic information, or any other basis protected by federal, state, or local law. TEGNA will reasonably accommodate qualified individuals with disabilities in accordance with applicable law.

Recruiting Fraud Alert:

To all candidates: your personal information and online safety are important to us. Only TEGNA Recruiters or Hiring Managers will reach out to you regarding consideration of your application or background.  Communications with TEGNA employees will either come from a TEGNA email address with a domain of tegna.com or one of our affiliate station domains.  

Recruiters or hiring managers will never request payments, ask for financial account information, or sensitive information such as social security numbers. 

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