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Remote Data Scientist Jobs in Beloit, WI (NOW HIRING)

Experity

Senior Data Engineer - Remote

Machesney Park, IL · On-site +1

$110K - $150K/yr

Remote: Team members who live within the U.S. but are not local within a commutable distance from ... You will work closely with Data Engineering, Data Science, Machine Learning, Product, and Software ...

Experity

Senior Data Engineer - Remote

Machesney Park, IL · On-site +1

$110K - $150K/yr

Remote: Team members who live within the U.S. but are not local within a commutable distance from ... You will work closely with Data Engineering, Data Science, Machine Learning, Product, and Software ...

micro1 AI

Clinical Pharmacy Technicians

Rockford, IL · Remote

$70 - $80/hr

Remote micro1 is engaging Pharmacovigilance Experts to contribute their advanced drug safety ... Author and review evaluation tasks based on DSURs, PSURs/PBRERs, and associated safety data and ...

micro1 AI

Pharmacovigilance Expert

Rockford, IL · Remote

$70 - $80/hr

Remote micro1 is engaging Pharmacovigilance Experts to contribute their advanced drug safety ... Author and review evaluation tasks based on DSURs, PSURs/PBRERs, and associated safety data and ...

micro1 AI

Medical Writing Manager

Rockford, IL · Remote

$50 - $80/hr

Remote micro1 is engaging Medical Writers / Clinical Document Authors to participate in a customer ... Evaluate scientific accuracy in narrative sections such as efficacy, safety summaries, discussion ...

micro1 AI

Medical Billing Specialist

Rockford, IL · Remote

$50 - $80/hr

Remote micro1 is engaging Medical Writers / Clinical Document Authors to participate in a customer ... Evaluate scientific accuracy in narrative sections such as efficacy, safety summaries, discussion ...

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Remote Data Scientist information

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$120K

$192.2K

How much do remote data scientist jobs pay per year?

As of Sep 8, 2026, the average yearly pay for remote data scientist in Beloit, WI is $120,040.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,300.00 and $133,000.00 per year, depending on experience, location, and employer.

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.

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 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.

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.

More about Remote Data Scientist jobs

What cities near Beloit, WI are hiring for Remote Data Scientist jobs?

Cities near Beloit, WI with the most Remote Data Scientist job openings:

Remote Data Scientist jobs near you
Infographic showing various Remote Data Scientist job openings in Beloit, WI as of August 2026, with employment types broken down into 86% Full Time, and 14% Part Time. Highlights an 100% Remote job distribution, with an average salary of $120,040 per year, or $57.7 per hour.

Senior Data Engineer - Remote

Experity

Machesney Park, IL • On-site, Remote

$110K - $150K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 25 days ago

Experity rating

8.5

Company rating: 8.5 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

81st of 247 rated software companies

Job description

Experity is a mission-driven team transforming on-demand healthcare across the U.S., empowering urgent care clinics with industry-leading software that makes care faster, easier, and more patient-focused. Joining us means doing meaningful work that directly improves the healthcare experience for millions-from helping families access care quickly to ensuring clinics run smoothly behind the scenes. If you want to make a real impact alongside innovative, dedicated teammates while contributing to a trusted platform that's becoming the operating system for on-demand care, Experity is the place to grow your career.
Why You'll Love Working Here
At Experity, great work starts with great people-and we go the extra mile to support our team with a culture of care, growth, and celebration:
  • Day-One Benefits: Health, dental/orthodontia, and vision coverage the moment you start.

  • Ownership & Impact: Be part of our success with a synthetic ownership program after one year.

  • Robust Support: Access our Employee Assistance Program for everything from mental wellness to financial coaching. Pets, planning a vacation, and more.

  • Recharge & Reconnect: Generous PTO, team events, family picnics, and holiday parties.

  • Career Growth: Development programs designed to help you thrive and grow.

  • Competitive Compensation: Including quarterly bonuses and 401(k) matching to invest in your future.

Position Type: Full-time
Compensation: $110,000-$150,000, based on experience
Location:
  • Remote: Team members who live within the U.S. but are not local within a commutable distance from one of our offices may work remotely, with occasional travel to an Experity office for meetings, team collaboration or as needed.

Position Overview
We are seeking a Senior Data Engineer to design, build, and operate scalable data pipelines and data platform capabilities that power Experity's analytics, AI/ML, and healthcare products.
This is a hands-on engineering role requiring strong expertise in data engineering, cloud technologies, distributed data processing, and software engineering. You will work closely with Data Engineering, Data Science, Machine Learning, Product, and Software Engineering teams to transform data from diverse sources into trusted, high-quality, and reusable data products.
As a senior member of the team, you will also provide technical leadership, mentor engineers, contribute to architecture and design decisions, and continuously improve the scalability, reliability, and efficiency of Experity's data ecosystem.
What You'll Do
Data Engineering & Platform
  • Design, build, and maintain scalable ETL/ELT pipelines for batch and near-real-time data processing.
  • Integrate data from databases, APIs, applications, event streams, and external sources into Experity's enterprise data platform.
  • Build reusable, high-quality data models and curated data products for analytics, reporting, AI/ML, and operational applications.
  • Develop complex data transformations and processing workflows using Python, SQL, Snowflake, and distributed data technologies.
  • Design data solutions for scalability, availability, resiliency, performance, and cost efficiency.

Engineering Excellence & DataOps
  • Develop reusable frameworks, libraries, and engineering patterns that improve developer productivity and data pipeline consistency.
  • Implement automated testing, CI/CD, Infrastructure as Code, and DataOps practices across data engineering workflows.
  • Build monitoring, alerting, data observability, and automated remediation capabilities to ensure pipeline reliability and data integrity.
  • Troubleshoot complex production issues and drive root-cause analysis and long-term improvements.
  • Continuously optimize data pipelines, queries, storage, and compute for performance and cost.

Data Quality, Governance & Security
  • Implement data quality, validation, lineage, and reconciliation controls across critical data pipelines.
  • Partner with Data Architecture, Governance, and Security teams to ensure data solutions follow enterprise standards.
  • Ensure healthcare data is handled securely and in accordance with applicable privacy, security, and compliance requirements.

Technical Leadership & Collaboration
  • Provide technical leadership through solution design, architecture discussions, code reviews, and engineering best practices.
  • Mentor Data Engineers and help improve engineering quality and technical capabilities across the team.
  • Partner with Data Scientists and Machine Learning Engineers to build reliable datasets, feature pipelines, and data infrastructure for AI/ML applications.
  • Collaborate with Product, Engineering, Analytics, and business stakeholders to translate requirements into scalable data solutions.
  • Maintain clear technical documentation for data pipelines, models, architecture, and operational processes.

Qualifications
  • Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related technical field.
  • 5+ years of experience building production-grade data pipelines, data platforms, and large-scale data processing solutions.
  • Advanced proficiency in Python and SQL with strong software engineering fundamentals.
  • Hands-on experience with Snowflake and cloud-based data platforms.
  • Experience with Kafka, Flink, or other distributed and streaming technologies.
  • Strong experience with AWS, including services such as S3, Lambda, Glue, Kinesis, or equivalent cloud technologies.
  • Experience designing and optimizing ETL/ELT pipelines, data models, and high-volume data processing workflows.
  • Experience with orchestration technologies such as Airflow or equivalent platforms.
  • Experience with CI/CD, Git, automated testing, and Infrastructure as Code.
  • Strong understanding of data quality, governance, security, observability, and production support.
  • Strong problem-solving, communication, and cross-functional collaboration skills.
  • A "full-stack mindset", not hesitating to do what it takes to solve a problem end-to-end

Preferred
  • Experience transforming data leveraging dbt, preferably dbt cloud.
  • Experience working in AI-native engineering environments and effectively leveraging AI-assisted development tools to improve engineering velocity, code quality, and operational efficiency.
  • Experience supporting Machine Learning and Generative AI workloads, including feature engineering and ML data pipelines.
  • Experience with Docker, Kubernetes, Terraform, or CloudFormation.
  • Experience with data cataloging, lineage, metadata management, and data observability platforms.
  • Experience in Healthcare, HealthTech, SaaS, or other regulated industries.

Why our team?
  • Build scalable data platforms that power healthcare products, analytics, Machine Learning, and Generative AI.
  • Solve challenging data problems involving large, complex, and highly valuable healthcare datasets.
  • Work with modern technologies including Snowflake, AWS, Python, Spark, and streaming platforms.
  • Collaborate closely with Data Engineering, Machine Learning, Data Science, Product, and Engineering teams.
  • Provide technical leadership while continuing to remain deeply hands-on with engineering.

Experity is committed to fostering a diverse, equitable, and inclusive workplace where innovation thrives through collaboration, diverse perspectives, and continuous learning.
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

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