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Remote Data Science Jobs in Chicago, IL (NOW HIRING)

Data Analyst

Chicago, IL · On-site +1

$95K - $110K/yr

Required Qualifications • Bachelor's degree in Data Science, Computer Science, Finance, or a ... Remote Work Opportunity About World Investment Advisors World Investment Advisors (formerly ...

Data Solutions Engineer

Chicago, IL · On-site +1

$91K - $156K/yr

Work with architects, operations teams, and data scientists to define data requirements and translate them into actionable data strategies. Design, build and optimize data systems for performance ...

Contribute to establishing standard methodologies for data science, including modeling, coding, analytics, and experimentation. * Leverage data to understand product performance and identify ...

Data Analytics Engineer

Chicago, IL · Remote

$118K - $141K/yr

Bachelor's or Master's degree in a quantitative discipline (e.g., Statistics, Computer Science, Mathematics, Physics, Data Science, Electrical Engineering, Information Systems) or equivalent ...

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Remote Data Science information

See Chicago, IL salary details

$24.1K

$107.3K

$204.8K

How much do remote data science jobs pay per year?

As of Jun 16, 2026, the average yearly pay for remote data science in Chicago, IL is $107,302.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,426.00 and $148,830.00 per year, depending on experience, location, and employer.

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

To thrive as a Remote Data Scientist, you need strong analytical skills, proficiency in statistics, and a solid background in mathematics or computer science, often supported by a relevant degree. Expertise in programming languages such as Python or R, familiarity with machine learning libraries, and experience with cloud-based data platforms are typically required. Excellent communication, self-motivation, and time management skills help you effectively collaborate and deliver results in a remote environment. These skills ensure accurate data analysis, meaningful insights, and successful teamwork despite physical distance.

How do remote data scientists typically collaborate with cross-functional teams to deliver insights?

Remote data scientists often work closely with product managers, engineers, and business analysts using digital collaboration tools such as Slack, Zoom, and project management platforms. Regular virtual meetings, code sharing via Git repositories, and clear documentation are essential to ensure alignment and transparency. While working remotely can present challenges in communication, proactive updates and scheduled syncs help foster strong teamwork and keep projects on track.

What is remote data science?

Remote data science refers to the practice of performing data analysis, modeling, and interpretation tasks from a location outside of a traditional office, such as from home or a co-working space. Remote data scientists use tools like Python, R, and SQL to analyze data, build predictive models, and communicate insights to stakeholders, all while collaborating virtually with their teams. This setup offers flexibility and can increase access to global job opportunities, but also requires strong self-motivation and communication skills to be effective.

Can a data scientist work fully remote?

Yes, many data scientists work fully remote, especially in companies that prioritize flexible work arrangements. Remote data science roles often require strong communication skills, proficiency with collaboration tools, and the ability to work independently on projects using programming languages like Python or R. However, some positions may require occasional in-person meetings or on-site presence depending on company policies.

Is 40 too late for data science?

Age is not a barrier to entering data science, and many professionals start or transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Will AI replace data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not eliminate the need for human expertise in interpreting results, designing models, and making strategic decisions. Data scientists will continue to be essential for developing complex algorithms, understanding business context, and ensuring ethical use of AI tools. Skills in programming, statistical analysis, and machine learning remain critical for the profession's evolving landscape.

What Are the Qualifications to Get a Remote Data Science Job?

The qualifications for a remote data scientist depend in large part on your employer and their industry. Most employers expect remote data science professionals to have at least a bachelor’s degree in statistics, math, computer science, or a related field. Some expect postgraduate degrees in a field like data mining or machine learning or demonstrable skills in these areas. As a remote worker, you need access to relevant programs and an internet connection. You may also want to pursue certification, such as becoming a Certified Analytics Professional (CAP).

What is the difference between Remote Data Science vs Remote Data Analyst?

AspectRemote Data ScienceRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; programming skills in Python/R; knowledge of machine learningDegree in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves building models and algorithmsData reporting, visualization, and interpreting data trends for decision-making
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, retail, finance, healthcare

Remote Data Science involves developing predictive models and advanced analytics, requiring programming and machine learning skills. Remote Data Analysts focus on interpreting data, creating reports, and visualizations. While both roles analyze data remotely, Data Scientists typically handle more complex modeling tasks, whereas Data Analysts focus on data interpretation and reporting.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this concept to focus on the most impactful variables, optimize models, and prioritize tasks for efficiency.
What are the most commonly searched types of Data Science jobs in Chicago, IL? The most popular types of Data Science jobs in Chicago, IL are:
What job categories do people searching Remote Data Science jobs in Chicago, IL look for? The top searched job categories for Remote Data Science jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Remote Data Science jobs? Cities near Chicago, IL with the most Remote Data Science job openings:
Infographic showing various Remote Data Science job openings in Chicago, IL as of June 2026, with employment types broken down into 2% As Needed, 73% Full Time, 21% Part Time, 2% Contract, and 2% Nights. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $107,302 per year, or $51.6 per hour.
Staff Software Engineer, Data Platform

Staff Software Engineer, Data Platform

Circle

Chicago, IL • On-site, Remote

Full-time

Posted 10 days ago


Job description

Circle (NYSE: CRCL) is one of the world's leading internet financial platform companies, building the foundation of a more open, global economy through digital assets, payment applications, and programmable blockchain infrastructure. Circle's platform includes the world's largest regulated stablecoin network anchored by USDC, Circle Payments Network for global money movement, and Arc, an enterprise-grade blockchain designed to become the Economic OS for the internet. Enterprises, financial institutions, and developers use Circle to power trusted, internet-scale financial innovation. Learn more at circle.com.

What you'll be part of:

Circle is committed to visibility and stability in everything we do. As we grow as an organization, we're expanding into some of the world's strongest jurisdictions. Speed and efficiency are motivators for our success and our employees live by our company values: High Integrity, Future Forward, Multistakeholder, Mindful, and Driven by Excellence. We have built a flexible work environment where new ideas are encouraged and everyone is a stakeholder.

Here is our team hierarchy for individual contributors:

Senior Software Engineer (III)

Staff Software Engineer (IV)

Your team is responsible for:

As a member of the Data Platform Engineering team, you own the core Data warehouse platform, data ingestion and processing, ETL/ELT pipelines orchestration platform, data cataloging, data governance. These components power our Product, Engineering, Analytics, and Data Science teams by enabling experimentation, operational excellence, and actionable insights to accelerate business growth.

You'll work on:

  • Design, build, and operate data platform services (warehousing, orchestration, and catalogs). Continuously enhance platform operations by improving monitoring, performance, reliability, and resource optimization.

  • Design, build and maintain batch and streaming data ingestion framework to source the required data for analytical and operational needs, which include onchain data, internal system data, and partner data.

  • Be a domain expert in streaming processing, data pipelines, data warehousing and quality. Work closely across multiple stakeholders-including Product, Engineering, Data Science, Security and Compliance teams-on data contract modeling, data lifecycle management, governance and regulatory/legal compliance.

  • Provide ML data platform capabilities for AI/Data Science teams to perform data preparation, model preparation and serving, and performance monitoring.

  • Develop and maintain core services and libraries to enhance critical platform functionalities, such as cataloging data assets and lineage, tracking data versioning and quality, managing auto-backfilling, implementing access controls on data assets.

You'll bring to Circle:

Senior Software Engineer (III):

  • 4+ years of software engineering experience building data-intensive systems

  • Hands-on experience designing and operating scalable batch, micro-batch, or streaming data pipelines

  • Experience in business domains such as payment systems, credit cards, bank transfers, or blockchains.

  • Familiarity with data governance, lineage, and provenance concepts

  • Strong understanding of open-source data technologies and cloud-native data platforms

  • Ability to tackle complex and ambiguous problems.

  • Self-starter who takes ownership and enjoys moving at a fast pace.

  • Excellent communication skills, with the ability to collaborate across multiple remote teams, share ideas and present concepts effectively.

Nice to have:

  • Experience with with streaming frameworks such as Apache Flink or Google Cloud Dataflow

  • Experience with NoSQL databases such as Bigtable, Cassandra

Staff Software Engineer (IV):

Includes all the requirements of a Senior Software Engineer, and:

  • 7+ years in software engineering experience for large-scale and complex data systems

  • Proven technical leadership in architecture and system design, influencing designs across multiple teams

  • Deep expertise in one or more of: streaming systems, data warehousing, data modeling, or large-scale ingestion platforms

  • Ability to identify high-impact technical opportunities independently and drive them from concept to production

  • Strong experience in:

    • Data platforms integrated with downstream consumers, tools, and services

    • Data quality, validation, and observability mechanisms across pipelines

  • Comfortable making and defending long-term architectural tradeoffs in ambiguous environments

Nice to have:

  • Hands-on Experience taking an operational, data-intensive application from initial design to production (01), or scaling and operating it at production scale.

  • Experience developing real-time analytics or near-real-time decisioning systems

Circle is on a mission to create an inclusive financial future, with transparency at our core. We consider a wide variety of elements when crafting our compensation ranges and total compensation packages.

Starting pay is determined by various factors, including but not limited to: relevant experience, skill set, qualifications, and other business and organizational needs. Please note that compensation ranges may differ for candidates in other locations.

Base Pay Range: $195,000-$257,500

We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status, or any other protected status required by the laws in the locations where we hire. Additionally, Circle participates in the E-Verify Program in certain locations, as required by law.

Should you require accommodations or assistance in our interview process because of a disability, please reach out toaccommodations@circle.comfor support. We respect your privacy and will connect with you separately from our interview process to accommodate your needs.

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