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Remote Meta Data Science Jobs in California (NOW HIRING)

Meta is seeking a Data Scientist to drive product strategy and decision-making across our family of applications, including Facebook, Instagram, Messenger, WhatsApp, and Meta's emerging platforms. In ...

In this role, you will collaborate with software engineering, data science, and product management teams to design/build scalable data solutions across Meta to optimize growth, strategy, and user ...

In this role, you will collaborate with software engineering, data science, and product management teams to design/build scalable data solutions across Meta to optimize growth, strategy, and user ...

In this role, you will collaborate with software engineering, data science, and product management teams to design/build scalable data solutions across Meta to optimize growth, strategy, and user ...

In this role, you will collaborate with software engineering, data science, and product management teams to design/build scalable data solutions across Meta to optimize growth, strategy, and user ...

In this role, you will collaborate with software engineering, data science, and product management teams to design/build scalable data solutions across Meta to optimize growth, strategy, and user ...

The Manager Data Science is responsible for architecting, building, and deploying production-grade ... This position is open to remote or hybrid. ESSENTIAL FUNCTIONS & RESPONSIBILITIES: * Design, build ...

Meta's Internal Audit team gives experienced auditors the opportunity to harness Meta's cutting ... Functional knowledge of Artificial Intelligence (traditional and Gen AI), data science, engineering ...

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Remote Meta Data Science information

What is the difference between Remote Meta Data Science vs Remote Data Analyst?

AspectRemote Meta Data ScienceRemote Data Analyst
Required CredentialsBachelor's or higher in Data Science, Computer Science, or related fields; knowledge of programming languages like Python or RBachelor's degree in Statistics, Mathematics, or related fields; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative remote teams, often with data science and engineering departmentsRemote work with focus on data reporting, visualization, and business insights
Employer & Industry UsageTech companies, e-commerce, finance, and healthcareMarketing agencies, retail, finance, and consulting firms

Remote Meta Data Science involves advanced data modeling, machine learning, and statistical analysis, often requiring programming skills and a strong technical background. Remote Data Analysts focus on interpreting data, creating reports, and visualizations to support business decisions. While both roles work remotely and require data handling skills, Meta Data Scientists typically engage in more complex modeling, whereas Data Analysts concentrate on data interpretation and presentation.

How does a remote Meta Data Science role typically collaborate with cross-functional teams despite being off-site?

In a remote Meta Data Science position, collaboration with cross-functional teams—such as product managers, engineers, and designers—is primarily facilitated through virtual communication tools like video conferencing, chat platforms, and collaborative project management software. Regular stand-ups, sprint meetings, and asynchronous updates help ensure alignment on project goals and timelines. While remote work offers flexibility, it also requires proactive communication and documentation to maintain transparency and foster effective teamwork. Building relationships remotely may take extra effort, but companies like Meta provide structured onboarding and virtual community events to support team cohesion.

What is a Remote Meta Data Scientist?

A Remote Meta Data Scientist is a professional who works for Meta (formerly Facebook) in the field of data science, but does so from a remote location instead of a traditional office. They analyze large datasets, build predictive models, and provide insights to help Meta improve its products and user experience. Their work may involve machine learning, statistical analysis, and collaborating virtually with cross-functional teams. Remote Meta Data Scientists use tools such as Python, SQL, and data visualization software to solve complex business problems.

What are the key skills and qualifications needed to thrive as a Remote Meta Data Scientist, and why are they important?

To thrive as a Remote Meta Data Scientist, you need strong analytical skills, expertise in statistics and machine learning, and a degree in a quantitative field such as computer science or mathematics. Proficiency with data science tools like Python, R, SQL, and platforms such as TensorFlow or PyTorch is typically required, along with experience using collaboration tools for remote work. Excellent communication, self-motivation, and problem-solving abilities are essential soft skills for remote collaboration and translating insights to stakeholders. These skills ensure you can independently deliver impactful data-driven solutions while effectively collaborating across distributed teams.
What are the most commonly searched types of Meta Data Science jobs in California? The most popular types of Meta Data Science jobs in California are:
What are popular job titles related to Remote Meta Data Science jobs in California? For Remote Meta Data Science jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Meta Data Science jobs in California look for? The top searched job categories for Remote Meta Data Science jobs in California are:
What cities in California are hiring for Remote Meta Data Science jobs? Cities in California with the most Remote Meta Data Science job openings:
Infographic showing various Remote Meta Data Science job openings in California as of June 2026, with employment types broken down into 66% Full Time, 31% Part Time, 2% Contract, and 1% Nights. Highlights an 75% Physical, 9% Hybrid, and 16% Remote job distribution.
Data Scientist II, Experimentation

Data Scientist II, Experimentation

Pinterest

San Francisco, CA • On-site, Remote

Other

Posted 25 days ago


Job description

We are seeking a data scientist with a strong background in experimentation and statistical analysis to help us improve and iterate on our experimentation platform. The successful candidate will play a key role in improving our experiment processes at scale, leveraging their expertise to drive innovation and help make sure that Pinterest users are receiving the most thoroughly data-driven features. With thousands of experiments running concurrently, the magnitude of our operations presents a significant opportunity for impact. If you possess a strategic mindset, proven experience in experimental design and analysis, and a passion for driving results, we invite you to join us in shaping the future of experimentation.

What you'll do:;

  • Comb through the literature in experimentation to identify potential methodologies that can improve parts of our platform where we have the biggest opportunities.
  • Make the process of setting up, running and evaluating experiments smoother and more repeatable for our platform users, ensuring that decisions are risk-aware and consistent
  • Write workflows to make our vast experimentation meta-data able to be leveraged by our team and outside of our team to better understand the experimentation landscape.
  • Consult with product data science teams to debug, design or improve their experiments and experimentation process.

What we're looking for:

  • PhD in a relevant field (stats, applied math, biostatistics, etc...) OR 2+ years of hands-on experience working as a data scientist or applied scientist.
  • Experience working directly on experimentation problems and an awareness of state of the art methodologies.
  • The ability to write clean, efficient, and scalable code that can be easily maintained and extended by other team members.
  • Proficiency in software development best practices, including version control systems such as Git, to ensure efficient collaboration, code management, and reproducibility in a data science environment.
  • Familiarity with workflow management tools such as Apache Airflow to create and schedule data pipelines, allowing for automated and reliable execution of machine learning workflows.

In-Office Requirement Statement:

  • We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
  • This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.

Relocation Statement:

  • This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

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