Senior Data Scientist, Ranking AI & Ads Analytics

Meta; Denver (CO); On-site; USD 177,000 - 247,000; Full time

Job summary

Meta seeks a Data Scientist in Ranking AI within the Monetization group to translate research into scalable production solutions for the Ads stack. You will leverage large, complex datasets to shape product opportunities and influence investment decisions through robust analytics and experimentation.

You will collaborate with Product, Engineering, Research, and Data teams to push forward modeling architectures, model-hardware co-design, and responsible AI practices while targeting high impact

Qualifications

• Experience with large and complex data sets to solve problems using analytical approaches.
• Ability to quantify product opportunities, forecast trends, and monitor metrics.
• Experience with SQL, Python, and R for data analysis and modeling.

Responsibilities

• Work with large data sets to solve a wide range of problems using analytical and statistical approaches.
• Apply quantitative analysis, experimentation, and data mining to develop product strategies that impact billions.
• Identify and measure success of product efforts through goals and metrics to guide roadmaps.
• Define opportunities and levers to improve products, driving insights and recommendations.
• Partner with Product, Engineering, and cross-functional teams to inform and execute strategy.

Skills

Data analysis

Statistical modeling

Experimentation

Data mining

Communication

Education

Bachelor's degree in Computer Science/Math

Master's or Ph.D. in quantitative field

Tools

SQL

Python

R

Job description

Meta seeks a Data Scientist in Ranking AI within the Monetization group to translate research into scalable production solutions for the Ads stack. You will leverage large, complex datasets to shape product opportunities and influence investment decisions through robust analytics and experimentation.

You will collaborate with Product, Engineering, Research, and Data teams to push forward modeling architectures, model-hardware co-design, and responsible AI practices while targeting high impact