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Economics Data Science Jobs (NOW HIRING)

Bachelor's degree in Analytics, Computer Science, Data Science, Operations Research, Economics, or a closely related field (or foreign education equivalent) and six (6) years of experience as a ...

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Economics Data Science information

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$41.5K

$142.5K

$201K

How much do economics data science jobs pay per year?

As of Jul 11, 2026, the average yearly pay for 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 economics majors work in data science?

Economics majors can work in data science roles, as their training in economic theory, statistical analysis, and quantitative methods provides a strong foundation. Success often depends on acquiring skills in programming languages like Python or R, data manipulation, and machine learning tools. Many data science positions value interdisciplinary knowledge, making economics a relevant background for analyzing and interpreting complex data sets.

What are common projects or responsibilities for professionals in Economics Data Science roles?

Economics Data Science professionals often work on projects that involve economic modeling, market analysis, and forecasting trends using large datasets. Typical responsibilities include gathering and cleaning economic data, developing predictive models, conducting statistical analyses, and translating results into actionable recommendations for business strategy or policy decisions. You may collaborate closely with economists, business analysts, and decision-makers to inform company direction or solve complex real-world problems. This role often involves a mix of independent data exploration and teamwork, offering opportunities to drive impactful results and shape organizational strategy.

What is economics data science?

Economics data science is a field that combines economic theory with data analysis and statistical methods to understand and solve economic problems. Professionals in this area use tools like Python, R, and econometrics to analyze large datasets, forecast trends, and inform policy or business decisions.

What are the key skills and qualifications needed to thrive in the Economics Data Science position, and why are they important?

To thrive in Economics Data Science, you need a strong background in economics, statistics, and programming (especially Python or R), often backed by a degree in economics, data science, or a related field. Proficiency with data analysis tools such as SQL, machine learning frameworks, and visualization software like Tableau is commonly required, and certifications in data science or analytics are advantageous. Excellent problem-solving abilities, communication skills, and a collaborative mindset help distinguish top performers in this position. These skills are crucial for effectively analyzing economic data, generating actionable insights, and conveying complex findings to both technical and non-technical stakeholders.

Is 40 too late for data science?

Economics Data Science is a field that values skills and experience over age; many professionals transition into data science later in their careers. Gaining proficiency in programming languages like Python or R, along with statistical knowledge, can facilitate entry regardless of age, and continuous learning is common in the industry.

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 market researcher. These positions often require skills in statistical analysis, programming (e.g., Python, R), and understanding economic principles to analyze data and inform decision-making.

What is an Economics Data Science job?

An Economics Data Science job combines economic theory, statistical analysis, and machine learning to interpret complex data and inform decision-making. Professionals in this field work with large datasets to analyze market trends, forecast economic conditions, and optimize business strategies. They commonly use programming languages like Python or R and tools such as SQL and econometric models. This role is valuable in industries like finance, government, and tech, where data-driven economic insights are crucial.

More about Economics Data Science jobs
What cities are hiring for Economics Data Science jobs? Cities with the most 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 Economics Data Science jobs? States with the most job openings for Economics Data Science jobs include:
Infographic showing various Economics Data Science job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Remote job distribution, with an average salary of $142,460 per year, or $68.5 per hour.
Director, Data Science: Data Science Tools

Director, Data Science: Data Science Tools

Liberty Mutual

Portsmouth, NH • On-site, Remote

$120K - $257K/yr

Full-time

Posted 25 days ago


Liberty Mutual rating

8.9

Company rating: 8.9 out of 10

Based on 144 frontline employees who took The Breakroom Quiz

33rd of 281 rated insurance


Job description


Description

The Data Science Infrastructure organization within USRM is hiring a Senior Technical Professional, Data Scientist to join the Data Science Tools team. This role will focus on improving the end-to-end modeling workflow for USRM Data Science by building internal tools, pipelines, and applications that streamline model development, evaluation, deployment, and iteration. The ideal candidate is highly technical, proactive, and motivated by building systems that help other data scientists work more efficiently.

**Candidates who live within 50 miles of Boston, MA; Portsmouth, NH; Seattle, WA; Columbus, OH; or Plano, TX will follow a hybrid schedule, coming into the office two days per week. Otherwise, this role is remote with occasional travel. **

Responsibilities:

  • Design and build internal tools, pipelines, and applications that improve model development, evaluation, and deployment
  • Own strategy and roadmaps for improving data science workflows and tooling across USRM
  • Design, build, and maintain Python packages used across the organization
  • Evaluate and implement AI agent capabilities in tooling using approaches such as MCP, RAG, PydanticAI, LangChain, or related frameworks
  • Work with workflow and modeling tools such as Luigi, Airflow, Celery, MLflow, H2O, scikit-learn, Optuna, and LightGBM, as well as Python development tools such as Pydantic, FastAPI, uv, ruff, and pytest
  • Promote MLOps and AI agent best practices in collaboration with groups such as Enterprise Data & Data Science
  • Stay current on developments in open-source data science frameworks, MLOps, and agentic coding practices
  • Help shape the direction of the Tools team and contribute to a culture of ownership, collaboration, and continuous improvement

The ideal candidate will have:

  • Professional experience building and maintaining Python-based data science or Machine Learning tooling used by multiple end users or teams
  • Worked with any of the following in a professional setting: Git, Bash/shell scripting, uv, pre-commit, ruff, pytest, or Pydantic
  • Built, deployed, or maintained workflows or pipelines using any of the following: Airflow, Luigi, Celery, Databricks, or MLflow
  • Implemented or supported AI/LLM-based tooling using frameworks such as PydanticAI, LangChain, MCP, or RAG
  • Developed, reviewed, or maintained internal Python packages, APIs, or data science applications using tools such as FastAPI, Streamlit, Dash, NiceGUI, or Plotly
  • Applied agentic AI techniques in day-to-day development and incorporate AI capabilities directly into tools and applications where they create meaningful value for data scientists
Qualifications
  • Broad knowledge of predictive analytic techniques and statistical diagnostics of models.
  • Advanced knowledge of predictive toolset; reflects as expert resource for tool development.
  • Demonstrated ability to exchange ideas and convey complex information clearly and concisely.
  • Ability to establish and build relationships within and outside the organization.
  • Ability to give effective training and presentations to management and other groups.
  • Ability to use results of analysis to persuade team, department management or senior management to a particular course of action.
  • Broad knowledge of business drivers and market context.
  • Has a value driven perspective with regard to understanding of work context and impact.
  • Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and a minimum of 3 years of relevant experience, a Master`s degree (scientific field of study) and a minimum of  6 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) and a minimum of  8 years of relevant experience.
About Us

Pay Philosophy: The typical starting salary range for this role is determined by a number of factors including skills, experience, education, certifications and location. The full salary range for this role reflects the competitive labor market value for all employees in these positions across the national market and provides an opportunity to progress as employees grow and develop within the role. Some roles at Liberty Mutual have a corresponding compensation plan which may include commission and/or bonus earnings at rates that vary based on multiple factors set forth in the compensation plan for the role.
At Liberty Mutual, our goal is to create a workplace where everyone feels valued, supported, and can thrive. We build an environment that welcomes a wide range of perspectives and experiences, with inclusion embedded in every aspect of our culture and reflected in everyday interactions. This comes to life through comprehensive benefits, workplace flexibility, professional development opportunities, and a host of opportunities provided through our Employee Resource Groups. Each employee plays a role in creating our inclusive culture, which supports every individual to do their best work. Together, we cultivate a community where everyone can make a meaningful impact for our business, our customers, and the communities we serve.
We value your hard work, integrity and commitment to make things better, and we put people first by offering you benefits that support your life and well-being. To learn more about our benefit offerings please visit: https://LMI.co/Benefits
Liberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran's status, pregnancy, genetic information or on any basis prohibited by federal, state or local law.
Fair Chance Notices

  • California
  • Los Angeles Incorporated
  • Los Angeles Unincorporated
  • Philadelphia
  • San Francisco

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About Liberty Mutual

Sourced by ZipRecruiter

Since 1912, we've grown into the fifth largest global property and casualty insurer based on 2022 gross written premium. We also rank 86 on the Fortune 100 list of largest corporations in the US based on 2022 revenue. ​At Liberty Mutual Insurance we work hard every day to support our customers and our people, so they can protect their families, build their businesses and invest in their futures. We are headquartered in Boston, but our people, our customers and our reach span the globe. So to better serve our global customers and employees, we are organized into three business units.

Industry

Insurance services

Company size

10,000+ Employees

Headquarters location

Boston, MA, US

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