Senior Data Analyst

Media.net; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Media.net is seeking a Data Analytics professional to monitor performance metrics, build reporting frameworks, and drive data-driven decision making across the Bidder and Ad Learning ecosystems.

You will analyze large-scale datasets, evaluate A/B tests, and collaborate with Product, Engineering, and Finance teams to optimize revenue and profitability.

Qualifications

• Strong foundation in statistics and experimental design.
• Experience with large-scale data analysis and reporting.

Responsibilities

• Monitor and analyze business, customer, and system performance metrics across the advertising ecosystem.
• Develop and manage reporting frameworks for actionable insights to stakeholders.
• Analyze large datasets to identify trends, opportunities, and inefficiencies in Bidder and Ad Learning funnels.
• Evaluate A/B test performance and provide data-driven recommendations to improve model outcomes and revenue.

Skills

SQL

Python

Excel

Statistics

A/B testing

PySpark

Communication

Data governance

Claude AI

Education

Bachelor's degree in Statistics/Mathematics/Economics

Tools

PySpark

Job description

About Us

Media.net is one of the world's leading companies in the Contextual Advertising space that provides a wide range of advertising and traffic monetization solutions. Since its founding, Media.net has constantly broken new ground in building innovative contextual advertising solutions. While our HQ is in Dubai, our employees are spread across key operation centers in New York, Los Angeles, Dubai, Zurich, Mumbai and Bangalore. Media.net is both large and small! It's got the culture of a startup with the stability and resources of a larger organization. We have a flat hierarchy, great perks and benefits, and an amazingly progressive culture.

About the Team

The Bidder platform processes over 5 billion ad impression requests daily from publishers across the globe. It determines whether an impression should be purchased and calculates its value using advanced machine learning models before submitting bids in real-time auctions. Multiple teams within the Bidder ecosystem continuously run A/B tests to optimize bidding strategies, model performance, revenue, and profitability.

Once an auction is won, the Ad Learning team determines the most relevant advertisement to display based on publisher, page content, and historical performance data. Leveraging sophisticated machine learning models, the team continuously improves ad selection and monetization outcomes through experimentation and data-driven optimization.

What You'll Be Doing

• Monitor and analyze business, customer, and system performance metrics across the advertising ecosystem.
• Develop and manage reporting frameworks that provide actionable insights to stakeholders and leadership teams.
• Analyze large-scale datasets to identify trends, opportunities, and inefficiencies within the Bidder and Ad Learning funnels.
• Evaluate A/B test performance and provide data-driven recommendations to improve model outcomes and revenue generation.
• Validate revenue reporting across multiple systems and ensure profitability calculations are accurate and reliable.
• Support the development and maintenance of Profit & Loss reporting frameworks and business financial analysis.
• Connect data across multiple teams and systems to create a coherent narrative that supports strategic decision-making.
• Investigate business queries related to data trends, user behavior, event timing, and system performance.
• Partner with cross-functional stakeholders to understand business challenges and provide analytical solutions.
• Evaluate potential features and enhancements for machine learning models using quantitative analysis.
• Prove or disprove business hypotheses through rigorous data analysis and statistical methods.
• Ensure data integrity, governance, normalization, and quality across reporting systems.
• Support business-critical processes, production data updates, and reporting enhancements.
• Contribute to the design and implementation of scalable data solutions that support organizational growth.

What We’re Looking For

• Bachelor's degree in Statistics, Mathematics, Economics, or a related quantitative discipline.
• 2-3 years of experience in Data Analytics, Business Analytics, or a related field.
• Strong proficiency in SQL with the ability to write complex queries and analyze large datasets.
• Hands-on experience with Python for data analysis and automation.
• Experience using AI-powered tools such as Claude AI to automate and enhance analytical workflows.
• Strong analytical and problem-solving skills with the ability to interpret complex datasets.
• Advanced Microsoft Excel skills.
• Excellent communication skills with the ability to present insights to both technical and non-technical stakeholders.
• Ability to manage multiple priorities in a fast-paced environment.
• Experience with PySpark or Spark query writing.
• Strong foundation in Statistics and Experimental Design.
• Experience working with A/B testing frameworks and experimentation platforms.
• Exposure to AdTech, Digital Advertising, Internet, or Data-driven technology businesses.
• Experience in data governance, reporting systems, and dashboard development.

What’s In It For You

• Delivering accurate and timely business and revenue insights.
• Improving reporting quality, data governance, and operational efficiency.
• Identifying and addressing funnel inefficiencies across bidding and ad-serving systems.
• Providing meaningful recommendations based on A/B test results and model performance.
• Enabling stakeholders to make faster, data-driven business decisions.
• Contributing directly to revenue growth and profitability optimization.
• Opportunity to work on systems that directly impact company revenue and profitability.
• Exposure to large-scale, real-time advertising and machine learning ecosystems.
• Ownership of high-impact analytics initiatives that influence business strategy.
• Opportunity to collaborate with Product, Engineering, Finance, and Business teams.
• Hands-on experience in experimentation, revenue optimization, and advanced data analytics.
• A dynamic environment that encourages innovation, learning, and growth while solving complex business problems at scale.