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Remote Meta Data Science Jobs in Phoenix, AZ (NOW HIRING)

Norstella

Senior Data Scientist

Phoenix, AZ · Remote

Remote, United States Date Posted: May 11, 2026 Employment Type: Full Time Job ID: R-1915 ... Job Summary Our dedicated Data Science team is at the forefront of revolutionizing pharma ...

SynergisticIT

Data Scientist

Tempe, AZ · On-site +1

With remote work and global talent pools, even entry-level roles receive hundreds of applications ... Recent graduates in Computer Science, Engineering, Math, Statistics, or related STEM fields

Sprouts Farmers Market

Data Scientist

Phoenix, AZ · Remote

Overview This is a fully remote opportunity. Sprouts is currently at the beginning of a journey to ... Bachelor's Degree in computer science, math or related field required * Ideal candidate would have ...

Sprouts Farmers Market

Data Scientist

Phoenix, AZ · Remote

Overview This is a fully remote opportunity. Sprouts is currently at the beginning of a journey to ... Bachelor's Degree in computer science, math or related field required * Ideal candidate would have ...

DataAnnotation

Decision Scientist

Phoenix, AZ · On-site +1

$40/hr

... remote work and setting your own schedule. We are looking for experienced quantitative ... Whether your background is in data science, astrophysics, economics, biostatistics, operations ...

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Remote Meta Data Science information

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$37.2K

$121.9K

$195.1K

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

As of May 28, 2026, the average yearly pay for remote meta data science in Phoenix, AZ is $121,868.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,800.00 and $135,000.00 per year, depending on experience, location, and employer.

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.

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 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.

What are popular job titles related to Remote Meta Data Science jobs in Phoenix, AZ? For Remote Meta Data Science jobs in Phoenix, AZ, the most frequently searched job titles are:
What job categories do people searching Remote Meta Data Science jobs in Phoenix, AZ look for? The top searched job categories for Remote Meta Data Science jobs in Phoenix, AZ are:
Remote Meta Data Science jobs near you
Data Science Manager - AI Trainer

Data Science Manager - AI Trainer

DataAnnotation

Phoenix, AZ • On-site, Remote

$60/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Join the DataAnnotation team and contribute to developing cutting‐edge AI systems, while enjoying the flexibility of remote work and setting your own schedule. We are looking for experienced quantitative professionals to help advance AI development. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real‐world quantitative experience to validate whether the outputs actually hold up in practice.

That's where you come in. As a member of DataAnnotation's team, you'll work closely with state‐of‐the‐art AI models on tasks like evaluating AI‐generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here.

Some team members fit this work alongside a full‐time role, while others treat it as their primary focus. To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand. Flexible schedule: choose which projects you take on and when you work. Competitive pay: projects are paid hourly, up to $60 USD/hour.

Impact: help shape the future of AI systems built to reason about data and analytics. Responsibilities Evaluate AI‐generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data‐driven insights, for technical accuracy and real‐world validity. Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.

Write clear technical explanations and well‐documented analytical code. Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning. Qualifications 2+ years of hands‐on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.

Some coding experience required, with comfort writing and reviewing analytical code end‐to‐end. Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time‐series forecasting). Fluency in English (native or bilingual level) with strong writing skills.

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise). Payment is made via PayPal.

We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. #J-18808-Ljbffr

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