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Remote Meta Data Science Jobs (NOW HIRING)

Meta's products are designed to bring people closer together and make it easier for them to share information, ideas, and experiences. We are hiring experienced Data Scientist across a variety of our ...

Meta's products are designed to bring people closer together and make it easier for them to share information, ideas, and experiences. We are hiring experienced Data Scientist across a variety of our ...

Meta's products are designed to bring people closer together and make it easier for them to share information, ideas, and experiences. We are hiring experienced Data Scientist across a variety of our ...

Meta's products are designed to bring people closer together and make it easier for them to share information, ideas, and experiences. We are hiring experienced Data Scientist across a variety of our ...

... Google, Meta, Mistral), including evaluation, benchmarking, and tradeoff analysis. * Model ... This role is fully remote for candidates who reside outside the 30 mile radius of one of our ...

As a Data Scientist at Meta, you will shape the future of people-facing and business-facing products we build across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp ...

As a Data Scientist at Meta, you will shape the future of people-facing and business-facing products we build across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp ...

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Remote Meta Data Science information

See salary details

$37.5K

$122.7K

$196.5K

How much do remote meta data science jobs pay per year?

As of Jul 11, 2026, the average yearly pay for remote meta data science in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

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.
More about Remote Meta Data Science jobs
What cities are hiring for Remote Meta Data Science jobs? Cities with the most Remote Meta Data Science job openings:
What are the most commonly searched types of Meta Data Science jobs? The most popular types of Meta Data Science jobs are:
What states have the most Remote Meta Data Science jobs? States with the most job openings for Remote Meta Data Science jobs include:
Infographic showing various Remote Meta Data Science job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

VP of Data Science (Remote)

Forbes Advisor

Wilmington, DE • On-site, Remote

Full-time

Posted 4 days ago


Job description

At Forbes Advisor, our mission is to help readers turn their aspirations into reality. We arm people with trusted advice and guidance so they can make informed decisions they feel confident in and get back to doing the things they care about most.
We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Forbes Advisor boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Forbes Advisor's global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel.
Our Data & Analytics organisation builds the products, platforms and intelligence that power every marketing, product and commercial decision across the business. We're looking for a Data Science leader who believes machine learning only creates value when it changes business decisions.
This is an opportunity to build and lead a commercially driven Data Science function that delivers measurable improvements in customer acquisition, marketing performance and long-term business growth.
You'll lead a growing team of Data Scientists while partnering closely with Engineering, Analytics, Product and Commercial teams to ensure predictive models become trusted, production-ready products that drive measurable commercial outcomes. As we continue investing in first-party data, AI, machine learning and advanced marketing measurement, we're looking for an experienced Data Science leader to help shape the next phase of our commercial Data Science capability.
Responsibilties:
  • Commercial Data Science: Lead the strategy and delivery of predictive models that improve customer acquisition, marketing performance and long-term commercial value. You'll shape capabilities including lifetime value modelling, propensity modelling, customer segmentation, forecasting and value-based bidding, ensuring every model is linked to measurable business outcomes.
  • Marketing Science & Decision Science: Partner with Marketing, Product and Commercial teams to apply Data Science to real business problems. You'll help define how predictive analytics, experimentation and AI improve campaign performance, customer understanding and strategic decision making across platforms including Google and Meta.
  • Production Data Science: Work closely with Engineering and ML Ops to ensure models become reliable, production-ready products rather than one-off analyses. You'll champion reproducible experimentation, scalable deployment, model monitoring, retraining strategies and continuous improvement throughout the model lifecycle.
  • Leadership & Stakeholder Management: Lead and develop a growing team of Data Scientists while building trusted relationships across the business. You'll translate complex modelling into clear commercial recommendations, influence senior stakeholders through evidence, and help establish Data Science as a trusted driver of business strategy and commercial growth.
  • Innovation & Industry Leadership: Represent Forbes in strategic conversations with technology partners including Google and Meta while staying connected to advances in AI, machine learning and marketing science. You'll evaluate emerging technologies, bring new ideas into the organisation and help ensure our Data Science capability remains commercially relevant and technically leading.

Qualifications:
  • Experience leading commercial Data Science, Marketing Science or Decision Science teams.
  • Strong expertise in predictive analytics, customer analytics, machine learning and statistical modelling.
  • Experience applying Data Science to marketing performance, customer acquisition, lifetime value or value-based bidding.
  • Experience productionising machine learning solutions within modern cloud environments and working closely with Engineering and ML Ops teams.
  • Strong understanding of SQL, Python and modern machine learning frameworks.
  • Experience working with Google Ads, Meta or other major advertising platforms.
  • Excellent stakeholder management and communication skills, with the ability to influence both technical and commercial audiences.
  • Experience building and developing high-performing Data Science teams.
  • Strong commercial judgement, balancing technical excellence with measurable business impact.
  • A pragmatic approach to AI, applying emerging technologies where they create genuine commercial value.

Nice to Have
  • Experience within affiliate marketing, digital publishing or lead-generation businesses.
  • Experience working in financial services, insurance or regulated industries.
  • Experience working directly with Google or Meta Data Science teams.
  • Experience with attribution modelling and marketing measurement.
  • Experience building optimisation algorithms for DSPs or advertising platforms.
  • Experience with causal inference, experimentation frameworks or incrementality testing.
  • Experience forecasting marketing or commercial performance.
  • Experience with Vertex AI or equivalent cloud-based machine learning platforms.

Forbes Advisor provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
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