2

Data Science Manager Remote Jobs in Utah (NOW HIRING)

Emphasizes translating business questions into analytical frameworks and connects data science to product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ...

Emphasizes translating business questions into analytical frameworks and connects data science to product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ...

Emphasizes translating business questions into analytical frameworks and connects data science to product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ...

Emphasizes translating business questions into analytical frameworks and connects data science to product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ...

Principal Data Scientist

Salt Lake City, UT · On-site +1

$131.75K - $178.25K/yr

The Principal Data Scientist will support Tendo analytics projects focused on quality management and risk adjustment. The person in this role will access data from multiple sources (public and ...

Senior Data Scientist

Salt Lake City, UT · On-site +1

$110.50K - $149.50K/yr

The Senior Data Scientist will support Tendo analytics projects focused on quality management and risk adjustment. The person in this role will access data from multiple sources (public and private ...

... remote work and setting your own schedule. We are looking for experienced quantitative ... Whether your background is in data science, astrophysics, economics, biostatistics, operations ...

AI Data Architect

Salt Lake City, UT · On-site +1

$83.20K - $178.80K/yr

However, the remote location must within the US. How you'll spend your time: * Define and implement ... Master's degree in Data Science, Information Management, or related discipline and at least 10 ...

next page

Showing results 1-20

Data Science Manager Remote information

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 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.

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 the most commonly searched types of Data Science Remote jobs in Utah? The most popular types of Data Science Remote jobs in Utah are:
What are popular job titles related to Data Science Manager Remote jobs in Utah? For Data Science Manager Remote jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Data Science Manager Remote jobs? Cities in Utah with the most Data Science Manager Remote job openings:
Infographic showing various Data Science Manager Remote job openings in Utah as of May 2026, with employment types broken down into 81% Full Time, 15% Part Time, 1% Temporary, and 3% Contract. Highlights an 65% Physical, 4% Hybrid, and 31% Remote job distribution.
Data Science Manager - AI Trainer

Data Science Manager - AI Trainer

DataAnnotation

Salt Lake City, UT • On-site, Remote

$40/hr

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

Join the DataAnnotation team and contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and setting your own schedule. We are looking for experienced quantitative professionals to help advance AI development. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real-world quantitative experience to validate whether the outputs actually hold up in practice.

That's where you come in. As a member of DataAnnotation's team, you'll work closely with state-of-the-art AI models on tasks like evaluating AI-generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here.

Some team members fit this work alongside a full-time role, while others treat it as their primary focus. To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand. Flexible schedule: choose which projects you take on and when you work. Competitive pay: projects are paid hourly, starting at $40+ USD per hour.

Impact: help shape the future of AI systems built to reason about data and analytics. Responsibilities Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity. Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.

Write clear technical explanations and well-documented analytical code. Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning. Qualifications 2+ years of hands‐on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.

Some coding experience required, with comfort writing and reviewing analytical code end-to-end. Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time‐series forecasting). Fluency in English (native or bilingual level) with strong writing skills.

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise). Note: Payment is made via PayPal.

We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. #datascience #J-18808-Ljbffr