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Full Time Nhl Data Science Jobs (NOW HIRING)

LiveRamp

Co-Op, Data Science

San Francisco, CA · On-site

$31 - $49/hr

You will receive the same orientation training as our full-time engineers, you will be matched with ... Work hand-in-hand with our data science and engineering teams to design and implement data models ...

Lemonade

Data Science Manager

New York, NY · On-site

$210K - $230K/yr

You'll sit within our Data Science team, owning the direction of a group of talented data ... Lemonade's US base salary range for this full-time position is $210,000 - $230,000 plus equity ...

LiveRamp

Co-Op, Data Science

San Francisco, CA

$31 - $49/hr

You will receive the same orientation training as our full-time engineers, you will be matched with ... Work hand-in-hand with our data science and engineering teams to design and implement data models ...

LiveRamp

Co-Op, Data Science

San Francisco, CA

$31 - $49/hr

You will receive the same orientation training as our full-time engineers, you will be matched with ... Work hand-in-hand with our data science and engineering teams to design and implement data models ...

Walmart

Director, Data Science

Fremont, CA

$169K - $338K/yr

... full-time and part-time associates in Walmart and Sam's Club facilities. Programs range from high ... Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science ...

Maximus

Data Science Manager

VA · On-site +1

General information Job Posting Title Data Science Manager Date Tuesday, May 12, 2026 City Remote Country United States Working time Full-time Description & Requirements Maximus is seeking a Data ...

Walmart

Director, Data Science

San Mateo, CA · On-site

$169K - $338K/yr

... full-time and part-time associates in Walmart and Sam's Club facilities. Programs range from high ... Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science ...

LiveRamp

Co-Op, Data Science

San Francisco, CA · On-site

$31 - $49/hr

You will receive the same orientation training as our full-time engineers, you will be matched with ... Work hand-in-hand with our data science and engineering teams to design and implement data models ...

College Board

Data Scientist, Data Science Team

This is a full-time position About the Team The Data Science team provides critical insights and tools to help the executive leadership team, technology teams, and business units optimize test ...

Evolver

Applied Data Science Intern

Palo Alto, CA · On-site

This is an intensive 10-week, full-time small cohort program designed to provide direct mentorship from experienced professionals in computer science, data science, artificial intelligence, and ...

Booz Allen Hamilton, Inc.

Data Science Engineer

Mclean, VA · On-site

$77K - $176K/yr

Data Science Engineer The Opportunity: As a Data Science Engineer, you'll help build advanced ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton

Data Science Engineer

Mclean, VA

$77K - $176K/yr

Data Science Engineer The Opportunity: As a Data Science Engineer, you'll help build advanced ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

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All JobsFull Time Nhl Data Science Jobs

Full Time Nhl Data Science information

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$46K

$165K

$243.5K

How much do full time nhl data science jobs pay per year?

As of Jun 15, 2026, the average yearly pay for full time nhl data science in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is a Full Time NHL Data Science job?

A Full Time NHL Data Science job involves using statistical analysis, machine learning, and data visualization to help National Hockey League (NHL) teams or organizations make data-driven decisions. Data scientists in this field analyze player performance, game statistics, and other data sources to provide insights that can improve team strategy, scouting, and player development. The role typically requires strong programming skills, knowledge of sports analytics, and the ability to communicate findings to coaches, managers, and executives. Full time positions offer stability, benefits, and the opportunity to work closely with hockey professionals throughout the season.

What are some common challenges faced by data scientists working full-time in the NHL, and how can they be addressed?

One common challenge for NHL data scientists is integrating diverse data sources, such as player tracking, game statistics, and scouting reports, into actionable insights for coaches and management. Balancing real-time analysis with long-term research projects also requires strong time-management and communication skills. Collaborating effectively within multidisciplinary teams—often including coaches, scouts, and IT professionals—helps ensure that complex models translate into practical, game-improving strategies. Staying updated with the latest sports analytics tools and methodologies further supports success in this dynamic role.

What are the key skills and qualifications needed to thrive as a Full Time NHL Data Scientist, and why are they important?

To thrive as a Full Time NHL Data Scientist, you need a strong background in statistics, data analysis, and programming, typically supported by a degree in mathematics, statistics, computer science, or a related field. Proficiency with data science tools such as Python, R, SQL, and machine learning frameworks, as well as experience with hockey analytics databases and visualization software, is essential. Strong communication, problem-solving, and teamwork skills help convey insights to coaches, analysts, and management effectively. These skills enable data-driven decision-making that can improve team performance and gain a competitive edge in the NHL.

What is the difference between Full Time Nhl Data Science vs Full Time Nhl Data Analyst?

AspectFull Time Nhl Data ScienceFull Time Nhl Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; programming skillsDegree in Analytics, Statistics, or related; basic data skills
Work EnvironmentCollaborative, research-focused, often involves modeling and machine learningOperational, reporting-focused, involves data interpretation and visualization
Employer & Industry UsageUsed by teams for predictive modeling, player performance analysis, strategic decisionsUsed for reporting, data tracking, and supporting game-day decisions

Full Time Nhl Data Science roles focus on advanced analytics, machine learning, and predictive modeling to inform strategic decisions. In contrast, Full Time Nhl Data Analysts primarily handle data reporting, visualization, and supporting day-to-day operations. Both roles require strong analytical skills, but Data Scientists typically have more technical expertise in programming and modeling, while Data Analysts focus on data interpretation and presentation.

More about Full Time Nhl Data Science jobs
What cities are hiring for Full Time Nhl Data Science jobs? Cities with the most Full Time Nhl Data Science job openings:
What are the most commonly searched types of Nhl Data Science jobs? The most popular types of Nhl Data Science jobs are:
What states have the most Full Time Nhl Data Science jobs? States with the most job openings for Full Time Nhl Data Science jobs include:
What job categories do people searching Full Time Nhl Data Science jobs look for? The top searched job categories for Full Time Nhl Data Science jobs are:
Full Time Nhl Data Science jobs near you
Infographic showing various Full Time Nhl Data Science job openings in the United States as of June 2026, with employment types broken down into 1% Locum Tenens, 1% As Needed, 93% Part Time, and 5% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Co-Op, Data Science

Co-Op, Data Science

LiveRamp

San Francisco, CA • On-site

$31 - $49/hr

Full-time

Posted 25 days ago

Job description

LiveRamp is the leading data connectivity platform. We believe connected data has the power to change the world. Our platform powers insights and experiences centered around the needs of real people, and in ways that keep the Internet open for all. LiveRampers thrive on building together with curiosity and humility-and have a good bit of fun along the way. We're always looking for smart, kind, and creative people to grow our team and impact.
Mission: LiveRamp makes it safe and easy for businesses to use data effectively.
Get ready for the best learning experience of your life. You will receive the same orientation training as our full-time engineers, you will be matched with an individual mentor, and you will be committing production code by the end of your first week. In the course of your internship or Co-op, you will be tasked with one or more mission-critical projects and make meaningful contributions to LiveRamp's success. Also, if our previous interns are any guides, you will have a ton of fun in the process!
Internships are 12 weeks long. Should we want to extend you a full-time offer after you graduate, we ask that you would be willing to consider this at the end of your internship.
Co-ops range between 12-24 weeks long. Should we want to extend you a full-time offer after you graduate, we ask that you would be willing to consider this at the end of your Co-op.
We are seeking Co-Op candidates interested in applying data science to the ad-tech space.
Join our Insights Engineering team!
You will:
  • Use statistical and ML based techniques to reduce selection bias, build representative samples, and analyze randomized studies in the ad-tech space.
  • Work hand-in-hand with our data science and engineering teams to design and implement data models that measure ad performance across large, disparate datasets.
  • Perform R&D work by prototyping new statistical and data modeling frameworks, translating prototypes into SQL and PySpark workflows, and then drive those prototypes into production.
  • Work in multiple cloud environments such as AWS and GCP, and help build, monitor, and troubleshoot automated modeling jobs using technologies such as Spark and BigQuery.
  • Troubleshoot internal and external models by understanding the key ingredients and underlying assumptions of the models.
  • Basic familiarity with prompt engineering and a proactive willingness to adopt new AI-driven productivity tools.

About you:
  • Possess strong mathematics, statistics and computer science skills that you are ready to turn into industry-ready skills
  • Pursuing or completed a degree in a Data Science related field (e.g. Mathematics, Statistics, Computer Science, Physics or other STEM degrees)
  • Excited to learn new data science techniques and technologies
  • Willing to dive in and learn by doing
  • Ready to work with others to solve hard problems
  • Possess a startup personality: smart, ethical, friendly, hard-working and proactive
  • Excited to work with products that have close interactions with customers

Preferred Skills:
  • Strong background in probability and statistics, experience implementing statistical models in SQL, and familiarity with fundamentals of randomized control trials.
  • Experience contributing to a mature Python-centric code base.
  • Strong command of common data science toolkits (Pandas, Numpy, Matplotlib, sci-kit learn).
  • Experience writing SQL and working with relational databases.
  • Understanding of software engineering fundamentals such as object oriented programming, computational complexity, version controlling with git, and experience in command line interfaces such as bash.
  • Knowledge of Big Data stacks such as Hadoop and Spark
  • Experience with AWS and/or GCP cloud providers
  • Experience with Agile software development

The approximate hourly base compensation range is $31.00 to $49.00. The actual offer, reflecting the total compensation package and benefits, will be determined by a number of factors including the applicant's experience, knowledge, skills, and abilities, geography, as well as internal equity among our team.
More about us:
LiveRamp's mission is to connect data in ways that matter, and doing so starts with our people. We know that inspired teams enlist people from a blend of backgrounds and experiences. And we know that individuals do their best when they not only bring their full selves to work but feel like they truly belong. Connecting LiveRampers to new ideas and one another is one of our guiding principles-one that informs how we hire, train, and grow our global team across nine countries and four continents. Click here to learn more about Diversity, Inclusion, & Belonging (DIB) at LiveRamp.
We use automated decision systems (ADS) as part of our recruitment and hiring process. If you require an accommodation or believe that the use of an ADS may create a barrier to your application or participation in the hiring process due to a disability or other protected characteristic, please let us know. We are committed to providing reasonable accommodations and ensuring an equitable hiring experience for all candidates.

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