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Remote Economics Data Science Jobs (NOW HIRING)

State of Iowa

Data Analyst - Part Time

Des Moines, IA · On-site +1

$29.97 - $46.49/hr

Four years of full-time work experience in business/data/statistical analytics, economic research, or data science. A total of four years of education and/or full-time experience (as described in ...

Crossing Hurdles

Financial Forecaster

Manhattan, NY · Remote

$105 - $140/hr

Remote Commitment: ~10-20 hours/week Role Responsibilities Generate probabilistic forecasts on ... Requirements Background in quantitative finance, trading, economics, or data science. Experience ...

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$41.5K

$142.5K

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

As of May 28, 2026, the average yearly pay for remote economics data science in the United States is $142,460.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,500.00 and $166,500.00 per year, depending on experience, location, and employer.

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

To thrive as a Remote Economics Data Scientist, you need a strong background in economics, statistics, and data analysis, typically supported by a degree in economics, statistics, or a related field. Proficiency in programming languages like Python or R, experience with data visualization tools, and familiarity with databases or cloud platforms are essential technical skills. Strong problem-solving abilities, effective communication, and self-motivation are vital soft skills for collaborating remotely and delivering actionable insights. These skills are crucial for accurately interpreting economic data, building predictive models, and driving data-informed decision-making in a remote environment.

How do remote Economics Data Science professionals typically collaborate with cross-functional teams?

Remote Economics Data Science professionals often work closely with teams in product, engineering, and business strategy through virtual meetings, shared dashboards, and collaborative tools. Communication is key, as they translate complex economic models and data findings into actionable insights for stakeholders with varying technical backgrounds. Regular check-ins, clear documentation, and participation in agile sprints or project cycles help align goals and ensure that data-driven recommendations are integrated into decision-making processes. Adapting to different time zones and building strong virtual relationships are important aspects of effective collaboration in this remote role.

What is a Remote Economics Data Scientist?

A Remote Economics Data Scientist is a professional who analyzes large sets of economic and financial data to extract insights, build predictive models, and support decision-making, all while working from a remote location. They combine expertise in economics, statistics, programming, and data analysis to interpret trends and inform business or policy strategies. Remote Economics Data Scientists often use tools such as Python, R, SQL, and data visualization platforms to communicate findings effectively. Their work can span industries like finance, government, consulting, and academia.
More about Remote Economics Data Science jobs
What cities are hiring for Remote Economics Data Science jobs? Cities with the most Remote Economics Data Science job openings:
What are the most commonly searched types of Economics Data Science jobs? The most popular types of Economics Data Science jobs are:
What states have the most Remote Economics Data Science jobs? States with the most job openings for Remote Economics Data Science jobs include:
What job categories do people searching Remote Economics Data Science jobs look for? The top searched job categories for Remote Economics Data Science jobs are:
Remote Economics Data Science jobs near you
Infographic showing various Remote Economics Data Science job openings in the United States as of May 2026, with employment types broken down into 4% Internship, 9% As Needed, 37% Full Time, 4% Part Time, and 46% Contract. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution, with an average salary of $142,460 per year, or $68.5 per hour.
Remote Data Science Consultant & AI Trainer

Remote Data Science Consultant & AI Trainer

DataAnnotation

Sioux Falls, SD • 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). Note: 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. #datascience #J-18808-Ljbffr

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