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Machine Learning Economics Jobs (NOW HIRING)

The ideal candidate for this role will bring a combination of experience in both economics and machine learning. We are in particular looking for current or recently graduated PhD students in ...

The Opportunity Adobe is looking for a Machine Learning Engineer who will apply AI and machine ... By using statistical and econometric methods, predictive models, experimental design methods, and ...

The Opportunity Adobe is looking for a Machine Learning Engineer who will apply AI and machine ... By using statistical and econometric methods, predictive models, experimental design methods, and ...

Ph.D. student in computer science, mathematics, statistics, economics, or related areas. * Strong programming (Python, Golang) and algorithmic skills. * Solid foundations in machine learning ...

Senior Machine Learning Engineer

$125K - $165K/yr

The Senior Machine Learning Engineer will implement machine learning standards and collaborate with ... Required : • Bachelor's degree in computer science, statistics, economics or related fields • ...

$86K - $119K/yr

MS or PhD in Computer Science, Statistics, Engineering, Economics, or related field. We also ... Proficiency with the Python machine learning stack, including tools such as Pandas, NumPy, and ...

Senior Machine Learning Engineer

Boston, MA · On-site +1

$113K - $155K/yr

MS or PhD in Computer Science, Statistics, Engineering, Economics, or related field. We also ... Proficiency with the Python machine learning stack, including tools such as Pandas, NumPy, and ...

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Machine Learning Economics information

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$53

$65

$75

How much do machine learning economics jobs pay per hour?

As of Jun 23, 2026, the average hourly pay for machine learning economics in the United States is $65.38, according to ZipRecruiter salary data. Most workers in this role earn between $59.62 and $71.15 per hour, depending on experience, location, and employer.

How much do economists in AI make?

Economists working in AI typically earn between $80,000 and $150,000 annually, depending on experience, education, and location. Those with specialized skills in machine learning, data analysis, and programming tools like Python or R tend to have higher salaries, especially in tech hubs or research institutions.

Is ML a high paying job?

Machine Learning roles are generally well-paid due to the specialized skills required, such as programming, statistics, and data analysis. Salaries vary based on experience, location, and industry, but many machine learning positions offer competitive compensation compared to other tech roles.

Will AI take econ jobs?

Machine Learning Economics involves applying AI and data analysis to economic problems, and while AI can automate certain tasks, it is unlikely to fully replace economists. Instead, AI tools are used to enhance economic research, modeling, and decision-making, requiring specialized skills in both economics and machine learning. Economists who adapt to these technologies can find new opportunities in data-driven analysis and policy development.

Is machine learning useful for economists?

Machine learning is increasingly valuable for economists, enabling them to analyze large datasets, identify patterns, and improve predictive models. Skills in programming languages like Python or R and understanding of statistical methods are essential for applying machine learning effectively in economic research and policy analysis.

What is the difference between Machine Learning Economics vs Data Scientist?

AspectMachine Learning EconomicsData Scientist
Required CredentialsDegree in Economics, Data Science, or related fields; knowledge of ML and economicsDegree in Computer Science, Statistics, or related fields; strong programming skills
Work EnvironmentResearch-focused, often in finance, tech, or consulting firmsData analysis, modeling, and visualization across various industries
Industry UsageFinance, tech, policy analysis, consultingTech, healthcare, finance, retail, and more

Machine Learning Economics combines economic theory with machine learning techniques to analyze market behaviors and policy impacts, often requiring knowledge of economics and ML. Data Scientists focus on extracting insights from data using statistical and ML methods across diverse industries. While both roles involve data analysis and programming, Machine Learning Economics emphasizes economic modeling, whereas Data Scientists have a broader scope in data-driven decision-making.

Infographic showing various Machine Learning Economics job openings in the United States as of June 2026, with employment types broken down into 14% Full Time, 85% Part Time, and 1% Nights. Highlights an 73% Physical, 7% Hybrid, and 20% Remote job distribution, with an average salary of $135,999 per year, or $65.4 per hour.
Machine Learning PhD Intern, Economics (Fall)

Machine Learning PhD Intern, Economics (Fall)

Instacart

OR

Other

Posted 3 days ago


Instacart rating

7.0

Company rating: 7.0 out of 10

Based on 30 frontline employees who took The Breakroom Quiz

31st of 62 rated delivery companies


Job description

Overview

We are looking for interns to join Instacart's Economics team. The ideal candidate for this role will bring a combination of experience in both economics and machine learning. We are in particular looking for current or recently graduated PhD students in economics or related fields like marketing, finance, or operations research. Candidates should bring some relevant research experience, typically in computationally intensive empirical topics, as well as some exposure to machine learning coursework and applications.

The Economics team at Instacart works on a range of interesting and challenging problems at the intersection of machine learning and economics, from aligning the incentives in our multi-sided marketplace to analyzing the impact of behavioral nudges on our customers' and shoppers' decisions. Some of the core areas of focus for our team include online advertising, uplift and long term value modeling, logistics, marketplace optimization (consumers, shoppers, retailers), inventory intelligence, and general causal inference. You can find more information in our blog post that introduces the team and the type of work we do.

About the Job

  • You will help design and build end-to-end machine learning solutions.
  • You will be working in small and cross-functional product teams, with great opportunities for growth and ownership of projects.
  • You will be an active member of an internal community, including economists, data scientists, operations research scientists and machine learning engineers, sharing learnings, best practices and research across many domains.
  • You will develop high impact solutions to support Instacart's ambitious growth plans.
  • You will work closely with engineers, product managers, other teams, and both internal and external stakeholders, owning a large part of the process from problem understanding to recommending a solution and testing it in controlled experiments.
  • You will have the freedom to suggest and drive organization-wide initiatives.

About You

Minimum Qualifications

  • Current or recently graduated PhD student in economics or a related field with focus on data-intense problems.
  • A blend of economic theory, applied econometrics, and business acumen that let you jump into a fast-paced environment and contribute from day one.
  • Expertise in causal inference with observational and experimental data.
  • Expertise in Python or R and fluency in data manipulation (SQL, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools.
  • Self-motivation and a strong sense of ownership

What Instacart employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Instacart logo

About Instacart

Sourced by ZipRecruiter

Instacart, based in San Francisco, CA, US, operates within the retail industry, specifically grocery delivery and pick-up service. It is recognized as a pioneer in this field, delivering fresh groceries from local stores directly to customers' doors. The company, which launched its services in 2012, continues to pioneer change in the online grocery shopping sector through its commitment to cutting-edge technology, new business ideas, and dedicated service.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

San Francisco, CA, US

Year founded

2012