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Remote Data Science Sports Jobs (NOW HIRING)

Proven experience in data science or a related field. * Proficiency in programming languages such ... Strong communication skills and the ability to work collaboratively in a remote environment. Salary ...

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 ...

The Data Science Manager will own pricing and risk strategy while leading a team of analysts and data scientists to optimize pricing initiatives across various sports and esports. Responsibilities ...

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 ...

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 Data Analysis & Manipulation: * Perform exploratory data analysis to identify patterns and opportunities in healthcare data

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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.

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.

Do data scientists work in sports?

Data scientists in sports analyze large datasets to improve team performance, player health, and game strategies. They use tools like Python, R, and machine learning techniques to extract insights from sports data, often working for teams, leagues, or sports analytics companies.

How much do sports data scientists make?

Sports data scientists typically earn between $70,000 and $120,000 annually, depending on experience, location, and the level of the organization. Entry-level roles may start lower, while experienced professionals or those working with major sports teams or organizations can earn higher salaries, especially with advanced skills in statistical analysis, machine learning, and programming tools like Python or R.

How much do NFL data scientists make?

NFL data scientists typically earn between $70,000 and $130,000 annually, depending on experience, education, and the complexity of projects. They often work with statistical software, machine learning tools, and sports analytics platforms in a collaborative environment.

Can data science jobs be done remotely?

Remote data science jobs, including roles in sports analytics, are common and often involve tasks such as data analysis, modeling, and visualization using tools like Python or R. Many companies offer remote positions to access a wider talent pool, and these roles typically require strong communication skills and familiarity with cloud-based collaboration platforms.

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.
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:
Infographic showing various Remote Data Science Sports job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

Full-time

Posted 6 days ago


Job description

Data Scientist nlp remote

Data Scientist to help revolutionize the healthcare industry with AI. This is a critical role where the right candidate will have the ability to work on a wide range of problems in the healthcare industry with an unparalleled amount of data.

Youll join a team focused on deep medical document understanding, extracting meaning, intent, and structure from unstructured medical and administrative records. Our mission is to build intelligent systems that can reliably interpret complex, messy, and high-stakes healthcare documentation at scale.

This role is a unique blend of applied machine learning, NLP, and product thinking. Youll collaborate closely with cross-functional teams to:

Design and develop models to extract entities, detect intents, and understand document structure
Tackle challenges like long-context reasoning, layout-aware NLP, and ambiguous inputs
Evaluate model performance where ground truth is partial, uncertain, or evolving
Shape the roadmap and success metrics for replacing legacy document processing systems with smarter, scalable solutions
We operate in a high-trust, high-ownership environment where experimentation and shipping value quickly are key. If youre excited by building systems that make healthcare data more usable, accurate, and safe, please reach out.

Qualifications

3+ years of experience with data science and machine learning in an industry setting, particularly in designing and building NLP models.
Proficiency with Python
Experience with the latest in language models (transformers, LLMs, etc.)
Proficiency with standard data analysis toolkits such as SQL, Numpy, Pandas, etc.
Proficiency with deep learning frameworks like PyTorch (preferred) or TensorFlow
Industry experience shepherding ML/AI projects from ideation to delivery
Demonstrated ability to influence company KPIs with AI
Demonstrated ability to navigate ambiguity
Bonus Experience

Experience with document layout analysis (using vision, NLP, or both).
Experience with Spark/PySpark
Experience with Databricks
Experience in the healthcare industry
Responsibilities

Play a key role in the success of our products by developing models for document understanding tasks.
Perform error analysis, data cleaning, and other related tasks to improve models.
Collaborate with your team by making recommendations for the development roadmap of a capability.
Work with other data scientists and engineers to optimize machine learning models and insert them into end-to-end pipelines.
Understand product use-cases and define key performance metrics for models according to business requirements.
Set up systems for long-term improvement of models and data quality (e.g. active learning, continuous learning systems, etc.).
After 3 Months, You Will

Have a strong grasp of technologies upon which our platform is built.
Be fully integrated into ongoing model development efforts with your team.
After 1 Year, You Will

Be independent in reading literature and doing research to develop models for new and existing products.
Have ownership over models internally, communicating with product managers, customer success managers, and engineers to make the model and the encompassing product succeed.
Be a subject matter expert on models and a source from which other teams can seek information and recommendations.

Data Scientist nlp remote

Data Scientist to help revolutionize the healthcare industry with AI. This is a critical role where the right candidate will have the ability to work on a wide range of problems in the healthcare industry with an unparalleled amount of data.

Youll join a team focused on deep medical document understanding, extracting meaning, intent, and structure from unstructured medical and administrative records. Our mission is to build intelligent systems that can reliably interpret complex, messy, and high-stakes healthcare documentation at scale.

This role is a unique blend of applied machine learning, NLP, and product thinking. Youll collaborate closely with cross-functional teams to:

Design and develop models to extract entities, detect intents, and understand document structure
Tackle challenges like long-context reasoning, layout-aware NLP, and ambiguous inputs
Evaluate model performance where ground truth is partial, uncertain, or evolving
Shape the roadmap and success metrics for replacing legacy document processing systems with smarter, scalable solutions
We operate in a high-trust, high-ownership environment where experimentation and shipping value quickly are key. If youre excited by building systems that make healthcare data more usable, accurate, and safe, please reach out.

Qualifications

3+ years of experience with data science and machine learning in an industry setting, particularly in designing and building NLP models.
Proficiency with Python
Experience with the latest in language models (transformers, LLMs, etc.)
Proficiency with standard data analysis toolkits such as SQL, Numpy, Pandas, etc.
Proficiency with deep learning frameworks like PyTorch (preferred) or TensorFlow
Industry experience shepherding ML/AI projects from ideation to delivery
Demonstrated ability to influence company KPIs with AI
Demonstrated ability to navigate ambiguity
Bonus Experience

Experience with document layout analysis (using vision, NLP, or both).
Experience with Spark/PySpark
Experience with Databricks
Experience in the healthcare industry
Responsibilities

Play a key role in the success of our products by developing models for document understanding tasks.
Perform error analysis, data cleaning, and other related tasks to improve models.
Collaborate with your team by making recommendations for the development roadmap of a capability.
Work with other data scientists and engineers to optimize machine learning models and insert them into end-to-end pipelines.
Understand product use-cases and define key performance metrics for models according to business requirements.
Set up systems for long-term improvement of models and data quality (e.g. active learning, continuous learning systems, etc.).
After 3 Months, You Will

Have a strong grasp of technologies upon which our platform is built.
Be fully integrated into ongoing model development efforts with your team.
After 1 Year, You Will

Be independent in reading literature and doing research to develop models for new and existing products.
Have ownership over models internally, communicating with product managers, customer success managers, and engineers to make the model and the encompassing product succeed.
Be a subject matter expert on Datavants models and a source from which other teams can seek information and recommendations.

Working Place:

NYC, New York, United States

Company
:


ESR Healthcare