Sr. Data Scientist Job at Meta (Menlo Park)

Sr. Data Scientist

Meta

Location:
United States , Menlo Park

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

304944.00 - 325270.00 USD / Year

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Job Description:

Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps and services like Messenger, Instagram, and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology.

Job Responsibility:

Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
Partner with Product and Engineering teams to solve complex problems and identify trends and opportunities
Inform, influence, support, and execute our product decisions and product launches
Work on Data Infrastructure
Working in Hadoop and Hive and MySQL
Authoring pipelines via SQL and python based ETL framework
Guide experimentation across the Core Ads Growth organization (~1,200 people for all functions)
This entails reviewing complex experiments across the Core Ads Growth product suite, and supporting the development of robust measurement plans across organizational pillars
Responsible for machine learning model development including guiding Machine Learning Engineers on the authoring of Machine Learning models such as guiding label design, and offline and online evaluation of results
Advancing analytics in Python and R leverage big data to make the right strategic business decisions, such as complex trade-offs between competing metrics, and steer product development for positive long-term outcomes for the business
The role, more specifically, involves the development and application of statistical methods to measure the long-term effects of changes and building key data sets to empower operational and exploratory analysis
Apply causal inference methodologies to analyze data and identify new opportunities for product changes
Designing and evaluating experiments, monitoring key product metrics, and understanding root causes of metrics changes
Building and analyzing dashboards and reports
Exploratory analysis is needed to understand users and what leads to positive long-term engagement
Working on roadmap building proposals and Understanding ecosystems, user behaviors, and long-term trends
Identifying levers to help move key metrics
Evaluating and defining metrics
Building models of user behaviors for analysis or to power production systems
Product Leadership and Influencing product teams through the presentation of work
Communicating the state of business, experiment results to product teams
Spreading best practices to analytics and product teams
Apply predictive modeling, machine learning, and experimentation / causal inference methods regularly to solve real life problems
5% International Travel Required

Requirements:

Bachelor's degree in Computer Science, Computer Engineering, Industrial engineering relevant technical field and five years of progressive, post-baccalaureate experience in the job offered or a computer-related occupation. Alternatively, the employer will accept 7 years of experience
Experience must include 5 years of experience in the following: Leading analytics work in IC capacity, working collaboratively with Engineering and cross-functional partners, and guiding data-influenced product planning, prioritization and strategy development
Applying predictive modeling, machine learning, and experimentation / causal inference methods on a regular basis to solve real life problems
Working effectively with a very large number of stakeholders, cross functionally, including Engineering, PM/TPM, Analytics & Finance as well as cross-org
Framing and communicating with senior leadership

What we offer:

bonus
equity
benefits

Additional Information:

Job Posted:
April 10, 2026

Employment Type:

Fulltime

Work Type:

On-site work

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