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Remote Data Science Sports Jobs (NOW HIRING)

Swish Analytics

Sports Data Analyst

San Francisco, CA · On-site +1

Company Description Swish Analytics is a sports analytics, betting and fantasy startup building the ... Department Data Science Role NFL Team Locations San Francisco, CA - Remote Remote status Fully ...

PrizePicks

Data Science Manager - Sports Pricing

Atlanta, GA · On-site +1

$160K - $190K/yr

... data scientists. * Oversee development and deployment of pricing models across major sports and ... S. and are willing to consider remote candidates. #LI-Remote Working at PrizePicks: The typical ...

Premise Health

Data Science Analyst - Remote

Brentwood, TN · On-site +1

$75K - $87K/yr

This is a Full Time, remote, Data Science Analyst role. What You'll Do * Analysis, Model Development & AI Solutions: * Perform exploratory data analysis to identify patterns and opportunities in ...

PatientPoint

REMOTE - Data Scientist

$101.54K - $175.73K/yr

Cincinnati OR Remote Travel Required: 2-3 times yearly Job Summary The Data Science team at PatientPoint works on business problems across the enterprise, such as provider growth, pricing, operations ...

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Remote Data Science Sports information

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

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 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 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.

More about Remote Data Science Sports jobs
What cities are hiring for Remote Data Science Sports jobs? Cities with the most Remote Data Science Sports job openings:
What are the most commonly searched types of Data Science Sports jobs? The most popular types of Data Science Sports jobs are:
What states have the most Remote Data Science Sports jobs? States with the most job openings for Remote Data Science Sports jobs include:
What job categories do people searching Remote Data Science Sports jobs look for? The top searched job categories for Remote Data Science Sports jobs are:
Remote Data Science Sports jobs near you
Infographic showing various Remote Data Science Sports job openings in the United States as of May 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 100% Remote job distribution.

Remote AI & Data Scientist for Clinical Intelligence & NLP

Alignment Healthcare

Manhattan, NY • Remote

$149.88K - $224.82K/yr

Full-time

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

Alignment Healthcare rating

7.3

Company rating: 7.3 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

207th of 259 rated insurance

Job description

Alignment Healthcare LLC is seeking a remote Data Scientist to enhance risk adjustment strategy within Medicare Advantage. The role involves building AI-powered tools for clinical documentation and working across teams to deploy impactful models. Candidates should have 2-5 years of experience in data science, a relevant Bachelor's degree, and proficiency in Python and SQL.

Competitive pay ranges from $149,882 to $224,823, based on experience and qualifications. #J-18808-Ljbffr

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