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Remote Economics Data Science Jobs in Riverside, CA

Reveel

Data Engineer (Remote)

Irvine, CA · Remote

$115K - $150K/yr

Bachelor's degree in Computer Science, Computer Engineering , or a related technical field (or ... Orchestrate data workflows with Dagster * Parse and process parcel logistics data in formats such ...

Cotality

Principal Software Engineer (Python)

Irvine, CA · On-site +1

$144K - $194K/yr

The hybrid-remote Principal Software Development Engineer leads the design, development, and ... Partner with the Data Science team to architect intelligent routing logic that leverages Small ...

Wayvia

Data Engineer III

Irvine, CA · On-site +1

$160K - $180K/yr

... Computer Science or related field or equivalent practical experience. * 5+ years of data ... This is a remote position open to candidates based in the United States. Compensation: The salary ...

Collectorsuniverse

Head of Fraud Operations

Santa Ana, CA · On-site +1

$139K - $200K/yr

For remote roles, and at our discretion, candidates may be asked to participate in an on-site ... Data Science on models; and builds the team, tooling, SLAs, and metrics that hold fraud losses down ...

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All JobsEconomics Data Science JobsRemote Economics Data Science JobsRemote Economics Data Science Jobs in Riverside, CA

Remote Economics Data Science information

See Riverside, CA salary details

$43.3K

$148.6K

$209.7K

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

As of Jul 10, 2026, the average yearly pay for remote economics data science in Riverside, CA is $148,624.00, according to ZipRecruiter salary data. Most workers in this role earn between $123,600.00 and $173,700.00 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.
What job categories do people searching Remote Economics Data Science jobs in Riverside, CA look for? The top searched job categories for Remote Economics Data Science jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for Remote Economics Data Science jobs? Cities near Riverside, CA with the most Remote Economics Data Science job openings:
Remote Economics Data Science jobs near you
Data Engineer (Remote)

Data Engineer (Remote)

Reveel

Irvine, CA • Remote

$115K - $150K/yr

Full-time

Re-posted 23 days ago

Job description

We are looking for a Data Engineer to help us expand and maintain our data infrastructure.

We're seeking a junior to mid-level Data Engineer to join our small but mighty team. This role is all about building and optimizing ETL workflows in Snowflake using Snowpark, managing parcel logistics data, and keeping our backend pipelines reliable. You'll be working directly with the CTO and will quickly get exposure to high-value projects that impact our core product.

This person should be familiar with Git and comfortable working in a backend-focused role. Experience with SQL and Python is still useful, but on the job you'll primarily be using Snowpark to write and orchestrate data transformations. Familiarity with workflow tools like Dagster is also a plus.

This role is fairly autonomous. A successful applicant should be comfortable using their skill, intuition, and creativity to accomplish a task without detailed direction on how it should be accomplished. While the ideal candidate should be capable and independent, they will be part of a supportive and friendly team dedicated to mutual success.

Minimum Requirements

  • Bachelor's degree in Computer Science, Computer Engineering, or a related technical field (or equivalent experience)

  • U.S. citizen and currently residing in the United States

Key Responsibilities

  • Develop and maintain ETL workflows in Snowflake using Snowpark

  • Write and optimize transformations to support reporting and analytics

  • Manage code in Git and contribute to a clean, well-documented codebase

  • Orchestrate data workflows with Dagster

  • Parse and process parcel logistics data in formats such as CSV, JSON, and EDI

  • Work directly with the CTO in 2-week sprint cycles

Preferred Skills

  • Snowflake (Snowpark)

  • Git

  • SQL

  • Python

  • Dagster (or similar orchestration tools like Airflow/dbt)

Bonus if Familiar With

  • Parcel logistics or shipping data

  • EDI feeds and schemas

  • Data pipelines in a SaaS product environment

About Us

We are the leading parcel shipping analytics company, pioneering Parcel Spend Management (PSM 2.0). Candidly, the logic behind shipping data is insane and very hard to understand! We make that easy for our customers by creating amazing software.

Since 2006, Reveel has been dedicated to providing Shipping Intelligence for the smartest business decisions possible. Founded by former DHL sales executives, Reveel was created to level the playing field. Over the past decade-plus, our zero-risk services have saved our clients millions of dollars.