About the role
The Senior Data Analyst will analyze large-scale datasets to uncover actionable insights and drive business impact across ad delivery and monetization systems. They will also partner with cross-functional teams to define KPIs, maintain data pipelines, and lead investigative analysis of performance anomalies.
What they look for
Requirements
Candidates must hold a bachelor's degree in a quantitative field such as Industrial Engineering, Economics, or Statistics. At least 3 years of experience in data analysis, high proficiency in SQL, and experience with BI tools and data warehouse technologies are required.
Full description
Appnext offers end-to-end discovery solutions covering all the touchpoints users have with their devices. Thanks to Appnext’s direct partnerships with top OEM brands and carriers, user engagement is achieved from the moment they personalize their device for the first time and throughout their daily mobile journey.
Appnext ‘Timeline’, a patented behavioral analytics technology, is uniquely capable of predicting the apps users are likely to need next. This innovative solution means app developers and marketers can seamlessly engage with users directly on their smartphones through personalized, contextual recommendations.
Established in 2012 and now with 12 offices globally, Appnext is the fastest-growing and largest independent mobile discovery platform in emerging markets.
We’re looking for a Senior Data Analyst to join our data-driven team at an ad-tech company that thrives on turning complexity into clarity. Our analysts play a critical role in transforming raw, noisy data into accurate, actionable signals that drive real-time decision-making and long-term strategy. You’ll work closely with product, engineering, and business teams to uncover insights, shape KPIs, and guide performance optimization.
Responsibilities:
- Analyze large-scale datasets from multiple sources to uncover actionable insights and drive business impact.
- Design, monitor, and maintain key performance indicators (KPIs) across ad delivery, bidding, and monetization systems.
- Partner with product, engineering, and operations teams to define metrics, run deep-dive analyses, and influence strategic decisions.
- Develop and maintain dashboards, automated reports, and data pipelines to ensure data accessibility and accuracy.
- Lead investigative analysis of anomalies or unexpected trends in campaign performance, traffic quality, or platform behavior.
Requirements
- BA / BSc in Industrial Engineering and Management / Information Systems Engineering / Economics / Statistics / Mathematics / similar background.
- 3+ years of experience in Data Analysis and interpretation (Marketing/ Business/ Product).
- High proficiency in SQL.
- Experience with data visualization of large data sets using BI systems (Qlik Sense, Sisense, Tableau, Looker, etc.).
- Experience working with data warehouse/data lake tools like Athena / Redshift / Snowflake /BigQuery.
- Knowledge of Python - An advantage.
- Experience building ETL processes – An advantage.
- Fluent in English both written and spoken - Must
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