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Remote Data Science Sports Jobs in Minnesota (NOW HIRING)

Power BI Data Engineer

Minneapolis, MN · 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 · 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 · 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 ...

You will partner with Data Engineering, Data Science, Architecture, Infrastructure, Security, and ... We embrace a remote-first culture through our Flexible Workplace. Most employees hold Home-Flex ...

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Showing results 21-40

Remote Data Science Sports information

What is a remote data science sports job?

A remote data science sports job involves analyzing sports-related data to extract insights, build predictive models, and support decision-making, all while working from a location outside of a traditional office, typically from home. Professionals in this role use statistical methods, programming, and machine learning to evaluate player performance, game strategies, or fan engagement. Their work helps sports teams, leagues, media companies, and betting firms make evidence-based decisions. Remote positions offer flexibility and often require strong communication skills to collaborate with teams virtually. The demand for these roles is growing as the sports industry increasingly relies on data-driven strategies.

What are the key skills and qualifications needed to thrive as a remote data science sports professional?

To thrive as a Remote Data Science Sports professional, you need a strong background in statistics, data analysis, and sports knowledge, often supported by a degree in mathematics, statistics, computer science, or a related field. Familiarity with programming languages such as Python or R, proficiency in data visualization tools, and experience with machine learning frameworks are typically required. Excellent problem-solving abilities, communication skills, and self-motivation are crucial soft skills for collaborating remotely and translating complex data into actionable insights. These skills ensure accurate sports data modeling, effective remote teamwork, and valuable contributions to decision-making in sports organizations.

How do remote data science professionals in the sports industry typically collaborate with coaches and analysts to turn data insights into actionable strategies?

Remote data science professionals in the sports industry often work closely with coaches, analysts, and other stakeholders through regular virtual meetings and collaborative platforms. They translate complex data findings into intuitive visualizations and reports, making it easier for non-technical team members to understand and apply insights. Communication and responsiveness are key, as data scientists may need to quickly adjust analyses based on feedback or new priorities from the sports staff. Building strong relationships and maintaining clear channels of communication help ensure that data-driven recommendations are effectively integrated into training, game strategies, and player development.

What is the difference between Remote Data Science Sports vs Remote Data Analysis Sports?

AspectRemote Data Science SportsRemote Data Analysis Sports
Required CredentialsBachelor's/Master's in Data Science, Statistics, or related fields; programming skills in Python/RBachelor's in Data Analysis, Statistics, or related fields; proficiency in Excel, SQL, and visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves modeling and machine learningData interpretation, reporting, and visualization, often in business contexts
Employer & Industry UsageTech companies, sports analytics firms, media outletsSports teams, media companies, sports analytics agencies

Remote Data Science Sports involves advanced modeling, machine learning, and statistical analysis, requiring higher technical credentials. Remote Data Analysis Sports focuses on interpreting data, creating reports, and visualizations. Both roles are common in sports industry analytics but differ in complexity and technical depth.

Can data science be used in sports?

Data science is widely used in sports to analyze player performance, optimize strategies, and improve team decision-making. Sports data analysts and data scientists utilize tools like machine learning, statistical models, and data visualization to gain insights and enhance athletic outcomes.

Do sports teams hire remote data scientists?

Some sports teams and organizations hire remote data scientists to analyze player performance, game strategies, and fan engagement using data analytics tools. These roles often require skills in statistical modeling, machine learning, and programming languages like Python or R, and may involve collaboration with on-site staff or remote work environments.

How much do remote data science sports make?

Remote data science roles in sports typically have salaries ranging from $70,000 to $130,000 annually, depending on experience, education, and the complexity of projects. Senior positions or those requiring specialized skills in machine learning or sports analytics can earn higher compensation, often exceeding $150,000. These roles often require proficiency in programming languages like Python or R and familiarity with sports data sources and analytics tools.

What job categories do people searching Remote Data Science Sports jobs in Minnesota look for?

The top searched job categories for Remote Data Science Sports jobs in Minnesota are:

Lead Data Engineer - Enterprise Data & Analytics - Remote

Mayo Clinic

Rochester, MN • On-site, Remote

$111K - $134K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 20 days ago


Mayo Clinic rating

7.8

Company rating: 7.8 out of 10

Based on 699 frontline employees who took The Breakroom Quiz

127th of 889 rated healthcare providers


Job description


Lead data design, prototype, and development of data pipeline architecture pipelines. Lead implementation of internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability. Lead cause analysis on external and internal processes and data to identify opportunities for improvement and answer questions. Excellent analytic skills associated with working on unstructured datasets. Understand the architecture, be a team player, lead technical discussions and communicate the technical discussion. Be a senior Individual contributor of the Data or Software Engineering teams. Be part of Technical Review Board along with Manager and Principal Engineer. Be a technical liaison between Manager, Software Engineers and Principal Engineers. Collaborate with software engineers to analyze, develop and test functional requirements. Serve as a hands-on technical leader who actively designs, develops, reviews, and optimizes production-grade data pipelines, data products, and platform capabilities. Maintain significant contribution to production codebases while establishing engineering standards, mentoring team members, and driving delivery of scalable, resilient solutions. Mentor and Coach Engineers. Work with team members to investigate design approaches, prototype new technology and evaluate technical feasibility. Work in an Agile/Safe/Scrum environment to deliver high quality software. Establish architectural principles, select design patterns, and then mentor team members on their appropriate application. Facilitate and drive communication between front-end, back-end, data and platform engineers. Play a formal Engineering lead role in the area of expertise. Keep up-to-date with industry trends and developments.
Key Responsibilities:
These positions are hands-on engineering roles. In this role, employees are expected to actively design, develop, review, and optimize production code and platform capabilities while providing technical leadership and mentorship to engineering teams.
Qualifications
Bachelor's Degree in Computer Science/Engineering or related field with 6 years of experience OR an Associate's degree in Computer Science/Engineering or related field with 8 years of experience. Knowledge of professional software engineering practices and best practices for the full software development life cycle (SDLC), including coding standards, code reviews, source control management, build processes, testing, and operations. Have in-depth knowledge of data engineering and building data pipelines with a minimum of 5 years of experience in data engineering, data science or analytical modeling and basic knowledge of related disciplines. Worked and lead Data Engineering teams in Continuous Integration / Continuous Delivery model. Build/Lead Data products highly resilient in nature. Build/Lead Test Automation suites, Unit Testing coverage, Data Quality, Monitoring & Observability. A minimum experience of 5 years using relational databases and NoSQL Databases. Experience with cloud platforms such as GCP, Azure, AWS.
Continuous Integration using Jenkins, Git Hub Actions or Azure Pipelines. Experience with cloud technologies, development and deployment. Experience with tools like Jira, GitHub, SharePoint, Azure Boards. Experience using advanced data processing solutions/capabilities such as Apache Spark, Hive, Airflow and Kafka, GCP Dataflow. Experience using big data, statistics and knowledge of data related aspects of machine learning. Experience with Google BigQuery, FHIR APIs, and Vertex AI. Knowledge of how workflow scheduling solutions such as Apache Airflow and Google Composer related to data systems. Knowledge of using Infrastructure as code (Kubernetes, Docker) in a cloud environment.
The preferred candidate will possess:
  • Advanced proficiency in Python and SQL with demonstrated experience building and supporting production-grade solutions.
  • Advanced experience designing and implementing scalable distributed computing solutions using technologies such as Spark, Flink, Ray, or comparable frameworks.
  • Deep understanding of cloud-agnostic architecture principles and modern data platform design.
  • Advanced experience with open data architecture technologies including Apache Iceberg, Delta Lake, and Apache Hudi.
  • Strong expertise with modern analytical data formats including Parquet, Avro, and ORC.
  • Experience designing data platforms that support analytics, AI/ML, and operational workloads at enterprise scale.
  • Experience implementing CI/CD, automated testing, Infrastructure-as-Code, observability, and engineering best practices.
  • Experience designing systems for scalability, reliability, security, resiliency, and long-term maintainability.

About Us
Why Mayo Clinic
Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans - to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic.
Benefits Highlights
  • Medical: Multiple plan options.
  • Dental: Delta Dental or reimbursement account for flexible coverage.
  • Vision: Affordable plan with national network.
  • Pre-Tax Savings: HSA and FSAs for eligible expenses.
  • Retirement: Competitive retirement package to secure your future.

About the Team
Just as our reputation has spread beyond our Minnesota roots, so have our locations. Today, our employees are located at our three major campuses in Phoenix/Scottsdale, Arizona, Jacksonville, Florida, Rochester, Minnesota, and at Mayo Clinic Health System campuses throughout Midwestern communities, and at our international locations. Each Mayo Clinic location is a special place where our employees thrive in both their work and personal lives. Learn more about what each unique Mayo Clinic campus has to offer, and where your best fit is.
Equal Opportunity
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, protected veteran status or disability status. Learn more about the "EOE is the Law". Mayo Clinic participates in E-Verify and may provide the Social Security Administration and, if necessary, the Department of Homeland Security with information from each new employee's Form I-9 to confirm work authorization.

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About Mayo Clinic

Sourced by ZipRecruiter

Mayo Clinic is the largest integrated, not-for-profit medical group practice in the world. We're building the future, one where the best possible care is available to everyone — and more people can heal at home. Our relentless research turns into earlier diagnoses and new cures. That's how we inspire hope in those who need it most. At Mayo Clinic, experts work together to solve the most challenging unmet needs of patients. Our history of innovation dates back almost 150 years, when brothers Will and Charlie Mayo pioneered an integrated, team-based approach to medicine. Today, that trailblazing spirit drives innovations like Mayo Clinic Platform — which powers new technologies to change how care is delivered to all.

Industry

Hospitals

Company size

10,000+ Employees

Headquarters location

Rochester, MN, US

Year founded

1919