Senior Data Scientist, Analytics & AI for Ranking

Meta; Baton Rouge (LA); On-site; USD 177,000 - 247,000; Full time

Job summary

Meta’s Ranking AI group is seeking a Data Scientist to power Ads stack analytics and model development. You will work with cross‑functional partners to translate data into product strategy, shape investment decisions, and influence roadmap priorities.

This role focuses on large, complex datasets and high-velocity production deployment. You will apply quantitative methods, experimentation, and data mining to drive revenue growth while collaborating with Product, Engineering, Research, and

Qualifications

• Bachelor’s degree in a relevant technical field or equivalent practical experience.
• 6+ years in analytics; PhD acceptable to reduce years requirement.
• Experience with SQL, Python, and/or R for data querying and analysis.
• Ability to translate data into actionable product insights.

Responsibilities

• Work with large and complex data sets to solve a wide array of challenging problems using analytical approaches.
• Apply quantitative analysis, experimentation, data mining, and data presentation to inform product strategies.
• Define and monitor product metrics to understand trends and measure success.
• Identify opportunities and drive roadmaps through insights and recommendations.
• Partner with product, engineering, and cross-functional teams to influence strategy and investments.

Skills

SQL

Python

R

Data analysis

Statistics

Education

Bachelor's degree in Computer Science / Computer Engineering or equivalent

Bachelor's degree in Mathematics / Statistics or equivalent

Master's or Ph.D. preferred

Job description

Meta’s Ranking AI group is seeking a Data Scientist to power Ads stack analytics and model development. You will work with cross‑functional partners to translate data into product strategy, shape investment decisions, and influence roadmap priorities.

This role focuses on large, complex datasets and high-velocity production deployment. You will apply quantitative methods, experimentation, and data mining to drive revenue growth while collaborating with Product, Engineering, Research, and