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Data Science Manager Remote Jobs in Sandy, UT (NOW HIRING)

Participate in remote assignments or attend on-site sessions when required * Follow project ... Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or ...

Support data science and model teams with platform needs, environment enablement, and deployment ... remote client service delivery. Recruiting for this role ends on 06/30/2026. Work you'll do As a ...

Senior Data Engineer

Draper, UT · On-site +1

$126K - $176K/yr

Excellent leadership, communication, and project management skills. Qualifications * Proven track ... Bachelor's or master's degree in computer science, informatics, data science or related technical ...

Data Engineers

Salt Lake City, UT · On-site +1

$110K - $133K/yr

The arrangement will be established in partnership with the manager and is subject to ongoing ... scientific discovery. This is a growth-focused role ideal for someone who thrives in a ...

... management. * Curriculum Awareness & Adaptive Instruction: Familiar with earth science curricula ... Adapts instruction using rock and mineral samples, weather data analysis, and interactive mapping ...

Staff Data Architect

Lehi, UT · On-site +1

$59.75 - $77/hr

NetDocuments is the world's #1 trusted cloud-based content management and productivity platform ... Two-time winner (2024, 2023) Top Workplace Innovation * 2025 Remote Work * 2024 Technology Industry ...

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Data Science Manager Remote information

See Sandy, UT salary details

$29.5K

$92.3K

$163.4K

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

As of Jun 22, 2026, the average yearly pay for data science manager remote in Sandy, UT is $92,313.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,700.00 and $119,300.00 per year, depending on experience, location, and employer.

What is the salary of a data science manager?

The salary of a data science manager typically ranges from $100,000 to $160,000 annually, depending on experience, location, and company size. Remote positions may offer competitive compensation aligned with industry standards and often include benefits such as bonuses and stock options.

Can a data scientist work fully remote?

Data science managers and data scientists often have the option to work fully remote, especially in companies that support remote work policies. Success in remote roles typically requires strong communication skills, proficiency with collaboration tools, and the ability to manage projects independently.

What is the 80 20 rule in data science?

The 80/20 rule in data science suggests that roughly 80% of results come from 20% of the efforts or features. Data science managers often focus on identifying the most impactful data, models, or features to optimize performance and efficiency in projects.

What does a remote Data Science Manager do?

A remote Data Science Manager oversees a team of data scientists, analysts, and engineers, ensuring that data-driven projects are successfully executed from a remote location. Their responsibilities include managing project timelines, providing technical guidance, mentoring team members, and aligning data initiatives with business goals. They also coordinate with other departments to implement data solutions, ensure data quality, and communicate results to stakeholders. Working remotely, they use digital tools to collaborate, monitor progress, and maintain team productivity.

Is 40 too late for data science?

Age is not a barrier to becoming a data science manager, as skills and experience are more important. Many professionals transition into data science roles later in their careers by acquiring relevant knowledge in programming, statistics, and machine learning. Continuous learning and practical experience can help individuals succeed regardless of age.

What are the key skills and qualifications needed to thrive as a Data Science Manager (Remote), and why are they important?

To thrive as a Data Science Manager in a remote setting, you need a robust background in statistics, programming (e.g., Python, R), machine learning, and a related degree, often supplemented by experience leading data teams. Familiarity with data analytics tools like SQL, cloud platforms (AWS, Azure), and project management software is typically required, along with certifications such as Certified Data Scientist or PMP. Strong leadership, communication, and collaboration skills are essential for managing distributed teams and aligning projects with business goals. These skills ensure effective project delivery, foster innovation, and maintain team cohesion in a virtual work environment.

How does a Data Science Manager working remotely typically collaborate with cross-functional teams?

As a remote Data Science Manager, effective collaboration with cross-functional teams—such as engineering, product, and business stakeholders—relies heavily on clear communication and efficient use of digital tools. Regular virtual meetings, project management platforms, and shared documentation are essential to align on objectives, share progress, and troubleshoot challenges. Building trust and fostering a culture of transparency helps ensure that remote data science teams stay connected and engaged with broader organizational goals, despite not sharing a physical workspace.

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

AspectData Science Manager RemoteData Analyst Remote
Required CredentialsBachelor's/Master's in Data Science, Statistics, or related field; experience with machine learning and leadershipBachelor's in Data Analysis, Statistics, or related field; proficiency in data visualization and SQL
Work EnvironmentLeads data science teams, manages projects, and develops models remotelyAnalyzes data, prepares reports, and supports decision-making remotely
Employer & Industry UsageTech companies, finance, healthcare, and e-commerceMarketing agencies, retail, finance, and consulting firms

The main difference is that Data Science Managers oversee data science teams and projects, requiring leadership skills and advanced technical knowledge, while Data Analysts focus on analyzing data and generating reports. Both roles can be remote and are in high demand across various industries.

What are popular job titles related to Data Science Manager Remote jobs in Sandy, UT? For Data Science Manager Remote jobs in Sandy, UT, the most frequently searched job titles are:
What job categories do people searching Data Science Manager Remote jobs in Sandy, UT look for? The top searched job categories for Data Science Manager Remote jobs in Sandy, UT are:

AI/ML Data Contributor

TSMG

Salt Lake City, UT • Remote

Full-time

Posted 24 days ago


Job description

Project Overview
We are currently hiring AI/ML Data Contributors to support a range of active and upcoming projects across the United States. In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing.

Projects may vary in scope and format, offering both remote and in-person opportunities (such as device or VR testing). This is a flexible, task-based role with the opportunity to participate in multiple projects over time.

Responsibilities
  • Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation
  • Participate in remote assignments or attend on-site sessions when required
  • Follow project guidelines and ensure high-quality task completion
  • Provide feedback and input during testing activities
  • Complete tasks within given timelines
Requirements
  • Must be based in the United States
  • Strong attention to detail and ability to follow instructions
  • Basic computer skills and familiarity with digital tools
  • Reliable internet connection and access to a computer or smartphone
  • Availability to participate in task-based work (schedule may vary)
Nice to Have
  • Previous experience in data annotation, QA, or testing
  • Interest in AI, machine learning, or emerging technologies
What We Offer
  • Paid, flexible task-based work
  • Opportunity to work on innovative AI/ML projects
  • Exposure to cutting-edge technologies (including device and VR testing)
  • Potential for ongoing project participation

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.