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Remote Economics Data Science Jobs (NOW HIRING)

Audiohook

Data Scientist

Eden, UT · On-site +1

Communicate clearly and proactively in a remote-first environment Qualifications Required * Bachelor\'s or Master\'s degree in Statistics, Economics, Data Science, Computer Science, or related ...

Cushman & Wakefield

Junior Data Scientist

Chicago, IL · On-site +1

This position will report to the Head of Data Science and Geospatial Analytics. The ideal candidate is a practitioner who thinks first like an economist, real estate analyst, or quantitative urban ...

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Remote Economics Data Science information

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$41.5K

$142.5K

$201K

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

As of Jul 11, 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.

Can data science jobs be done remotely?

Remote economics data science jobs are common, allowing professionals to work from anywhere with internet access. These roles often require skills in programming, data analysis, and tools like Python or R, and may involve collaboration through online platforms. Many companies now offer flexible or fully remote positions for data scientists.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. For a remote economics data scientist, focusing on the most impactful variables or data sources can improve model efficiency and accuracy.

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.

What jobs can I get with data science and economics?

With a background in data science and economics, you can pursue roles such as economic analyst, data scientist, financial analyst, policy analyst, or research associate. These positions often require skills in statistical analysis, programming (e.g., Python, R), and understanding economic models, and they are common in finance, government, consulting, and research organizations.

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.

Can I be a data scientist with an economics degree?

A data scientist role often requires strong skills in statistics, programming, and data analysis, which can be gained with an economics degree. Many data scientists have backgrounds in economics, especially if they have experience with tools like Python, R, or SQL, and knowledge of machine learning techniques. Additional certifications or coursework in data science can enhance employability in this field.
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:
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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 July 2026, with employment types broken down into 50% Internship, and 50% Full Time. Highlights an 100% Remote job distribution, with an average salary of $142,460 per year, or $68.5 per hour.
Data Scientist

Data Scientist

Audiohook

Eden, UT • On-site, Remote

Full-time

Medical, Dental, Vision, PTO

Posted 16 days ago

Job description

Role Overview

The Data Scientist will own the measurement science behind Audiohook\'s performance audio advertising platform. You\'ll design and run incrementality tests, build and maintain marketing mix models, and apply causal analysis to quantify how Audiohook drives outcomes for advertisers. This role combines hands-on modeling with the opportunity to shape how we prove value to customers, sharpen our bidding and optimization systems, and influence product direction. You\'ll collaborate closely with Engineering, Product, Sales, and Customer Success to ensure measurement isn\'t just statistically sound but operationally useful.

Key ResponsibilitiesMarketing Measurement & Causal Inference

  • Design and run incrementality experiments (geo, ghost bidding, holdout, PSA) that quantify Audiohook\'s lift for advertisers

  • Build, maintain, and evolve marketing mix models (MMM) and multi-touch attribution analyses across customer campaigns

  • Apply causal inference methods — difference-in-differences, synthetic controls, instrumental variables, propensity scoring — to questions that can\'t be answered with RCTs

  • Translate measurement results into clear narratives for advertisers, internal stakeholders, and the product team

Modeling & Analysis

  • Partner with Engineering on the data and modeling layer that powers bidding, pacing, and optimization decisions

  • Develop and validate predictive models that improve campaign performance and platform efficiency

  • Instrument experiments and analyses for reproducibility, monitoring, and ongoing measurement quality

Cross-Functional Collaboration

  • Partner with Sales and Customer Success on measurement studies for priority accounts and renewals

  • Partner with Product on roadmap inputs grounded in causal evidence, not just descriptive data

  • Present findings to advertisers, internal teams, and leadership in clear, decision-ready formats

  • Communicate clearly and proactively in a remote-first environment

QualificationsRequired

  • Bachelor\'s or Master\'s degree in Statistics, Economics, Data Science, Computer Science, or related quantitative field

  • 3–5 years of applied data science experience with a focus on marketing measurement — incrementality, MMM, attribution, or causal analysis

  • Hands-on experience designing and analyzing experiments (A/B, geo, holdout) in a marketing or advertising context

  • Strong fluency in Python (pandas, statsmodels, scikit-learn, PyMC, or similar) and SQL

  • Solid grounding in statistical inference, regression, and causal methods

  • Ability to communicate technical results to non-technical audiences — advertisers, sales, leadership

  • Excellent attention to detail and intellectual honesty about model limitations

Preferred

  • Experience in adtech, digital advertising, or media measurement

  • Experience with Bayesian methods or Bayesian MMM frameworks (e.g., PyMC-Marketing, LightweightMMM, Robyn)

  • Experience working with large-scale ad event data (impressions, clicks, conversions) and modern data stacks (e.g., Iceberg, Snowflake, BigQuery)

  • Experience in a startup or high-growth company

  • Comfort using AI tools to accelerate exploratory analysis, code, and write-ups while maintaining methodological rigor

What We Offer

  • Fully remote work environment

  • Competitive salary and equity opportunities

  • Performance bonuses

  • Health, dental, and vision benefits

  • Other benefits such as daily lunch stipend, monthly wifi, cell phone and subscription reimbursement, and annual hardware stipend

  • Flexible PTO and remote-friendly culture

  • Bi-annual Corporate Offsites

  • Opportunity to help shape a function at a rapidly scaling tech company

Apply