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Remote Data Scientist Jobs in Minnesota (NOW HIRING)

Data Engineer

Minneapolis, MN ยท On-site +1

$90K - $113K/yr

The successful candidate will work cross-functionally with data architects, AI/ML engineers, data scientists, analysts, and domain experts to design and implement modern data engineering solutions.

Power BI Data Engineer

Minneapolis, MN ยท On-site +1

$119K - $143K/yr

This position is remote with preference to align to one of Legence' s office locations. Key ... Understanding of data science concepts and predictive analytics Technical Environment * Power BI ...

Power BI Data Engineer

Minneapolis, MN ยท On-site +1

$119K - $143K/yr

This position is remote with preference to align to one of Legence' s office locations. Key ... Understanding of data science concepts and predictive analytics Technical Environment * Power BI ...

Power BI Data Engineer

Minneapolis, MN ยท On-site +1

$119K - $143K/yr

This position is remote with preference to align to one of Legence' s office locations. Key ... Understanding of data science concepts and predictive analytics Technical Environment * Power BI ...

Power BI Data Engineer

Minneapolis, MN ยท On-site +1

$119K - $143K/yr

This position is remote with preference to align to one of Legence' s office locations. Key ... Understanding of data science concepts and predictive analytics Technical Environment * Power BI ...

Significant experience in AI/ML engineering with a strong data science background. * Demonstrated ... Supportive and flexible working environment, allowing remote work from anywhere.

Bachelor's degree in Computer Science, Information Systems, or related field (or equivalent ... We embrace a remote-first culture through our Flexible Workplace. Most employees hold Home-Flex ...

Showing results 41-60

Remote Data Scientist information

See Minnesota salary details

$36.7K

$120.2K

$192.5K

How much do remote data scientist jobs pay per year?

As of Aug 7, 2026, the average yearly pay for remote data scientist in Minnesota is $120,211.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,500.00 and $133,200.00 per year, depending on experience, location, and employer.

What key skills and qualifications are 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, usually demonstrated through a relevant degree. Familiarity with programming languages like Python or R, experience with machine learning frameworks, and knowledge of data visualization tools are typically required, along with certifications such as Microsoft Certified: Azure Data Scientist Associate or Google Professional Data Engineer. Excellent communication, problem-solving abilities, and self-motivation are critical soft skills for collaborating remotely and delivering insights to stakeholders. These skills are crucial for effectively analyzing data, building predictive models, and driving data-driven decisions in a distributed work environment.

What does a remote data scientist do?

Remote data scientists collect, confirm, and interpret data to determine useful information for their employer. Unlike in-house data scientists, remote data scientists work outside the office, either from home or another location with Wi-Fi accessibility. Remote data scientists help organizations identify patterns and trends in their data to provide information about lucrative opportunities, necessary improvements, and potential innovations. The information they get from the records they gather helps businesses make decisions in critical areas, such as product development, sales and marketing techniques, and client retention. You find remote data scientists in many different industries, including pharmaceuticals, manufacturing, and banking.

What is a remote data scientist?

Remote data scientists are professionals who analyze and interpret complex data while working outside of a traditional office environment, typically from home or another remote location. They use statistical methods, machine learning, and programming to extract insights from data, helping organizations make data-driven decisions. Remote data scientists collaborate with teams virtually, often using tools for communication, data analysis, and project management. This flexible work arrangement allows for talent from anywhere to contribute to companies worldwide, provided they have reliable internet and the necessary technical skills.

How does a remote data scientist typically collaborate with team members across different time zones?

As a remote data scientist, effective collaboration across time zones often involves leveraging asynchronous communication tools like Slack, project management platforms, and version control systems such as Git. Regular virtual meetings are scheduled to accommodate overlapping hours, and clear documentation becomes crucial for keeping everyone aligned. Proactive communication, sharing progress updates, and setting clear expectations help ensure seamless teamwork despite geographical differences. This structure allows remote data scientists to contribute meaningfully while maintaining flexibility in their work schedules.

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

AspectRemote Data ScientistRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; often requires programming skills in Python or RDegree in Analytics, Business, or related field; may require proficiency in Excel, SQL, and visualization tools
Work EnvironmentResearch-focused, developing models, machine learning, and predictive analyticsData interpretation, reporting, and visualization to support business decisions
Employer & Industry UsageTech companies, finance, healthcare, and e-commerceRetail, marketing, finance, and consulting firms

Remote Data Scientists focus on building models and advanced analytics, while Remote Data Analysts interpret data and create reports. Both roles require strong analytical skills but differ in technical depth and project scope.

What are the most commonly searched types of Data Scientist jobs in Minnesota? The most popular types of Data Scientist jobs in Minnesota are:
What are popular job titles related to Remote Data Scientist jobs in Minnesota? For Remote Data Scientist jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Remote Data Scientist jobs in Minnesota look for? The top searched job categories for Remote Data Scientist jobs in Minnesota are:
What cities in Minnesota are hiring for Remote Data Scientist jobs? Cities in Minnesota with the most Remote Data Scientist job openings:
Infographic showing various Remote Data Scientist job openings in Minnesota as of August 2026, with employment types broken down into 78% Full Time, and 22% Contract. Highlights an 100% Remote job distribution, with an average salary of $120,211 per year, or $57.8 per hour.

Data Engineer

Ryan Companies

Minneapolis, MN โ€ข On-site, Remote

$90K - $113K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted yesterday


Job description

Job Description:

Ryan Companies has an immediate need for a Data Engineer. This is an IN-OFFICE opportunity (4 days per week, 1 day work-from-home) in our Minneapolis headquarters office.

The Data Engineer will play a foundational role in building and maintaining the data infrastructure that enables advanced analytics, machine learning, and decision intelligence across Ryan Companies. This role will focus on developing scalable, reliable data pipelines that ensure the quality, accessibility, and performance of data used across all of Ryan.


The successful candidate will work cross-functionally with data architects, AI/ML engineers, data scientists, analysts, and domain experts to design and implement modern data engineering solutions.

What you can expect to do:

Data Architecture and Modeling

  • Architect, build, and maintain scalable data pipelines on Google Cloud Platform (GCP), utilizing services like BigQuery, Dataflow, and Cloud Storage to handle diverse data sources (e.g., project systems, safety logs, IoT/sensor data).

  • Design and implement effective data models, including star schemas and dimensional modeling, to support business intelligence and analytics.

  • Develop and manage data solutions to ensure efficient data storage, retrieval, and cost-effectiveness.

  • Contribute to metadata management, data cataloging, and lineage tracking to enhance the discovery and transparency of enterprise data assets.

Data Pipeline Development and Management

  • Design and orchestrate robust ETL/ELT processes and data integration workflows using tools like Cloud Composer or Apache Airflow.

  • Implement and manage both batch and real-time data streaming pipelines to ensure timely and accurate data availability for downstream applications.

  • Write clean, efficient, and well-documented Python and SQL code to process and transform large, complex datasets.

  • Monitor, troubleshoot, and optimize data pipeline performance, identifying and resolving bottlenecks to improve efficiency and scalability.

Data Quality and Governance

  • Implement and maintain data quality frameworks to ensure the accuracy, consistency, and reliability of data across all systems.

  • Develop and implement data validation and testing procedures to maintain the highest standards of data integrity.

  • Establish and enforce data governance policies and best practices, ensuring all data handling is secure, private, and compliant with regulations.

Platform Engineering and Automation

  • Build and maintain CI/CD pipelines for the automated testing and deployment of data engineering workflows.

  • Support the deployment and monitoring of machine learning models by implementing reproducible and traceable data environments.

  • Partner with DevOps and Technology teams to automate infrastructure provisioning, CI/CD processes, and data quality monitoring.

Collaboration and Leadership

  • Partner with Enterprise Architects, Solution Architects, data scientists, and analysts to understand data needs, design technical solutions, and translate business requirements into architectural designs.

  • Lead the implementation of data solutions, from discovery and design through to deployment.

  • Collaborate with other data engineers, fostering a culture of knowledge sharing and continuous improvement.

  • Create and maintain clear documentation for architecture, schemas, and pipeline workflows to support team knowledge and onboarding.

What we expect you should have:

  • Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related technical field.

  • 3+ years of professional experience in data engineering or a similar role.

  • Strong programming skills in Python, SQL, with experience using tools such as Cloud Composer.

  • Proven experience designing and maintaining data pipelines using platforms such as GCP, AWS, Azure or similar.

Preferred Skills:

  • Experience building data infrastructure and services in cloud-native environments (GCP preferred).

  • Exposure to domain-driven architecture.

  • Strong collaboration and communication skills with a track record of partnering across functions to deliver high-impact solutions.

Compensation:

The base pay range is $90,000-$113,000/Annually. The salary may vary within the anticipated range based on factors such as the ultimate location of the position and the selected candidate's knowledge, skills, and abilities. Position may be eligible for additional compensation that may include commission and/or an incentive program.

Eligibility:

Position requires verification of employment to work in the U.S.

Benefits:

  • Competitive Salary

  • Medical, Dental and Vision Benefits

  • Retirement and Savings Benefits

  • Flexible Spending and Health Savings Accounts

  • Life Insurance

  • Short-Term and Long-Term Disability

  • Educational Assistance

  • Paid Time Off (PTO)

  • Employee Assistance and Wellness Programs

  • Parenting Benefits

  • Employee Discount Programs

  • Pet insurance

  • Ryan Foundation - charitable matching funds

  • Paid Time for Volunteer Events

Disclaimer: Eligibility may vary based on factors such as role, hours worked, employment status, length of service, location, and other considerations. Detailed information will be shared with eligible candidates during the hiring process, and the official terms and conditions will be outlined in each individual offer document.

Ryan Companies is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.


Notice to Candidates:

Please be advised that initial outreach regarding employment at Ryan Companies will only occur via email from the domain @ryancompanies.com email address. If you recieve communication from someone you believe is impersonating Ryan Companies, please report it to us at humanresources@ryancompanies.com

Non-Solicitation Notice to Recruitment Agencies:

Ryan Companies kindly requests that recruitment agencies and third-party recruiters do not submit unsolicited resumes or candidate information to any Ryan Companies employee or office. Ryan Companies will not be responsible for any fees or expenses associated with unsolicited submissions. If recruitment services are required, we will reach out directly to agencies on our approved vendor list. We appreciate your understanding and cooperation.