Company Background
Our client is a global technology company transforming the way brands and agencies make marketing decisions. Its platform enables marketers to plan and activate cross-channel, programmatic media campaigns using real-time research, proprietary audience data, advanced analytics, and more than 150 integrated partners including Facebook, Instagram, Pinterest, Snapchat, and Twitter. The company operates across North America, Europe, the Middle East, Asia, and Australia.
Project Description
Our client’s Automatic Content Recognition (ACR) platform identifies TV content and advertisements viewed on Smart TVs across multiple countries and content sources, including linear TV, streaming platforms, live OTT, and ads. The platform processes billions of viewing events and fingerprints, transforming them into structured viewing sessions and audience insights used for advertising, measurement, analytics, and data licensing products. The ecosystem includes distributed systems for device data collection, ingestion, content matching, session-building, metadata enrichment, and customer-facing data products. The Data Analyst will help validate, monitor, and improve data quality and business insights by working closely with Product, Engineering, Commercial teams, and Leadership.
Technologies
SQL, Python
Statistical analysis, A/B testing
Large-scale data analysis, exploratory data analysis
Data quality validation, data visualization
Data warehousing
What You’ll Do
Own and develop a deep understanding of key ACR datasets, including how data is generated, processed, matched, enriched, and consumed by downstream products;
Monitor data quality, identify anomalies, investigate unexpected metric changes, and explain their root causes and business impact;
Analyze changes in audience numbers, match rates, session counts, station coverage, customer results, and other key operational and business metrics;
Determine whether data behavior is expected, caused by product or engineering changes, or requires corrective action;
Partner with Product Management on feature validation, experiment evaluation, business impact assessment, opportunity identification, and product requirement support;
Work closely with Engineering teams to validate releases, measure the impact of algorithm changes, identify production anomalies, and support root cause investigations;
Design and improve analytical validation frameworks, reporting, monitoring, alerting, and automation to increase trust in data quality and analytical outputs;
Support stakeholders and data consumers by answering dataset-related questions and translating complex data behavior into clear business insights;
Job Requirements
4+ years of experience in data analytics, product analytics, data science, or a similar analytical role;
Advanced SQL skills and experience working with large-scale datasets;
Experience using Python for data analysis, exploration, validation, and automation;
Strong statistical analysis skills, including the ability to interpret trends, anomalies, experiments, and business impact;
Experience with exploratory data analysis, data quality validation, and root cause investigation;
Understanding of experiment design and A/B testing concepts;
Experience with data visualization and ability to present analytical findings clearly to technical and non-technical stakeholders;
Understanding of data warehousing concepts and how analytical datasets are structured, transformed, and consumed;
Ability to take ownership of complex datasets, proactively identify risks, anomalies, and data quality issues, and work independently with minimal direction;
Strong business understanding, curiosity, attention to detail, and clear communication skills;
English level: B2 or higher;
Nice to have
Experience with Metaflow or similar workflow orchestration tools;
Experience with Jupyter or similar analytical notebooks;
Understanding of ETL systems and distributed data process
