2

Full Time Nhl Data Science Jobs (NOW HIRING)

Job Type Full-time Description Join the ADVI Health Data Science Talent Community About Us ADVI Health: Expert Advice. Clear Vision. Are you passionate about turning data into action, and insights ...

This role blends deep data science expertise with program analysis, enabling the organization to ... Regular and reliable attendance on a full time basis [or in accordance with posted schedule]

Director, Data Science

New York, NY · On-site +1

$215K - $409K/yr

The Role As a Data Scientist at Kyndryl you are the bridge between business problems and innovative ... S. is $215,640 to $409,800 based on a full-time schedule. Your actual compensation may vary ...

The Role As a Data Scientist at Kyndryl you are the bridge between business problems and innovative ... S. is $215,640 to $409,800 based on a full-time schedule.Your actual compensation may vary ...

next page

Showing results 1-20

Full Time Nhl Data Science information

See salary details

$46K

$165K

$243.5K

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

As of Jul 13, 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:
Infographic showing various Full Time Nhl Data Science 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, with an average salary of $165,018 per year, or $79.3 per hour.
Data Science Associate Manager

Data Science Associate Manager

PepsiCo

Manhattan, NY

$120K - $205K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 26 days ago


PepsiCo rating

7.5

Company rating: 7.5 out of 10

Based on 865 frontline employees who took The Breakroom Quiz

143rd of 395 rated food and drinks producers


Job description

Overview

We’re seeking a Data Science Manager to lead a high-performing team delivering scalable analytics and machine learning solutions. In this role, you will drive the technical vision, execution, and adoption of data science initiatives that support our global Strategy and Transformation agenda. You will partner closely with business and technology leaders to identify high-impact opportunities and foster a strong data-driven culture.


Responsibilities
  • Lead, mentor, and grow a team of data scientists, providing technical guidance and career development
  • Own the end-to-end delivery of large-scale analytics and machine learning initiatives
  • Define standards and best practices for model development, data pipelines, and ML production workflows
  • Oversee the design, deployment, monitoring, and optimization of machine learning systems in production
  • Partner with business stakeholders to translate strategic goals into data science roadmaps and measurable outcomes
  • Drive adoption of modern techniques, including Generative AI, where they deliver clear business value
  • Communicate technical concepts, progress, and impact effectively to business and technical audiences

Compensation and Benefits:

  • The expected compensation range for this position is between $120,300 - $205,150.
  • Location, confirmed job-related skills, experience, and education will be considered in setting actual starting salary. Your recruiter can share more about the specific salary range during the hiring process.
  • Bonus based on performance and eligibility target payout is 10% of annual salary paid out annually.
  • Paid time off subject to eligibility, including paid parental leave, vacation, sick, and bereavement.
  • In addition to salary, PepsiCo offers a comprehensive benefits package to support our employees and their families, subject to elections and eligibility: Medical, Dental, Vision, Disability, Health, and Dependent Care Reimbursement Accounts, Employee Assistance Program (EAP), Insurance (Accident, Group Legal, Life), Defined Contribution Retirement Plan.

Qualifications
  • Master’s Degree in Data Science, Computer Science, Statistics, or equivalent
  • 5+ years of experience in data science, with leadership or people-management responsibility
  • Proven experience delivering machine learning solutions using diverse data sources
  • Strong Python skills and ability to guide production-quality ML code
  • Solid understanding of software engineering, data engineering, and MLOps best practices
  • Experience with deep learning frameworks (TensorFlow or PyTorch)
  • Strong foundation in statistical and mathematical modeling
  • Experience with cloud-based and distributed computing platforms
  • Experience with Generative AI, including LLMs, prompt engineering, and RAG architectures

EEO Statement

Our Company will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the Fair Credit Reporting Act, and all other applicable laws, including but not limited to, San Francisco Police Code Sections 4901-4919, commonly referred to as the San Francisco Fair Chance Ordinance; and Chapter XVII, Article 9 of the Los Angeles Municipal Code, commonly referred to as the Fair Chance Initiative for Hiring Ordinance.

All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.

PepsiCo is an Equal Opportunity Employer: Female / Minority / Disability / Protected Veteran / Sexual Orientation / Gender Identity / Age.

If you'd like more information about your EEO rights as an applicant under the law, please download the available EEO is the Law & EEO is the Law Supplement documents. View PepsiCo EEO Policy.

Please view our Pay Transparency Statement

Qualifications:
  • Master’s Degree in Data Science, Computer Science, Statistics, or equivalent
  • 5+ years of experience in data science, with leadership or people-management responsibility
  • Proven experience delivering machine learning solutions using diverse data sources
  • Strong Python skills and ability to guide production-quality ML code
  • Solid understanding of software engineering, data engineering, and MLOps best practices
  • Experience with deep learning frameworks (TensorFlow or PyTorch)
  • Strong foundation in statistical and mathematical modeling
  • Experience with cloud-based and distributed computing platforms
  • Experience with Generative AI, including LLMs, prompt engineering, and RAG architectures
Education:UNAVAILABLEEmployment Type: FULL_TIME

What PepsiCo employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


PepsiCo logo

About PepsiCo

Sourced by ZipRecruiter

PepsiCo products are enjoyed by consumers more than one billion times a day in more than 200 countries and territories around the world. PepsiCo generated $86 billion in net revenue in 2022, driven by a complementary beverage and convenient foods portfolio that includes Lay's, Doritos, Cheetos, Gatorade, Pepsi-Cola, Mountain Dew, Quaker, and SodaStream. PepsiCo's product portfolio includes a wide range of enjoyable foods and beverages, including many iconic brands that generate more than $1 billion each in estimated annual retail sales.

Industry

Food and drink manufacturing

Company size

10,000+ Employees

Headquarters location

Purchase, NY, US

Year founded

1965