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Remote Data Science Jobs in Hopkins, MN (NOW HIRING)

Data Engineer

Minneapolis, MN · 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.

Join our global in-house technology team of more than 5,000 engineers, data scientists, architects, and product managers who are striving to make Target the most convenient, safe, and joyful place to ...

... a remote position. In this role, you will have the opportunity to: * Partner with Operating ... Bachelor's degree in Computer Science, IT, Data Science, or Business/Data Analytics * 5+ years of ...

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Remote Data Science information

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.

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 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 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.

Can I work remotely as a data scientist?

Yes, many data scientist roles are available as remote positions, especially in companies that prioritize flexible work arrangements. Remote data scientists typically need strong skills in programming, data analysis, and tools like Python or R, and may require familiarity with cloud platforms and collaboration tools. Availability depends on the employer's policies and the specific job requirements.

What are the most commonly searched types of Data Science jobs in Hopkins, MN?

The most popular types of Data Science jobs in Hopkins, MN are:

What job categories do people searching Remote Data Science jobs in Hopkins, MN look for?

The top searched job categories for Remote Data Science jobs in Hopkins, MN are:

What cities near Hopkins, MN are hiring for Remote Data Science jobs?

Cities near Hopkins, MN with the most Remote Data Science job openings:

Infographic showing various Remote Data Science job openings in Hopkins, MN as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 14% Part Time, 3% Contract, and 1% Nights. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Data Engineer

Ryan Companies

Minneapolis, MN • On-site, Remote

$90K - $113K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 16 days ago


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.