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Remote Nhl Data Analytics Jobs in Virginia (NOW HIRING)

ICF is seeking an experienced Data Analytics Manager to lead enterprise data, analytics, governance ... This position is remote within the United States. Please note that ICF monitors employee work ...

The Data Analytics Architect leads the design, integration, and governance of data systems that ... FAA Part 107 Remote Pilot Certification (required) Physical Requirements / Working Conditions ...

Data Analysis and Insight: 30% * Conduct in-depth data analysis and experimentation to uncover ... Onsite or remote: 60% onsite * Vision: Daily be able to see and read computer screen and other ...

Senior Engineer - Data Analytics

VA ยท On-site +1

$106K - $144K/yr

This is a remote position. Essential Duties and Responsibilities: - Responsible for delivery of ... data and semantic model design. - Analyze requirements and apply architectural and engineering ...

Provide consulting relating to the data mining and analysis of data from a range of sources to ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

Provide consulting relating to the data mining and analysis of data from a range of sources to ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

Data Scientist

Springfield, VA ยท Remote

$120K - $160K/yr

TS/SCI with Poly Potential for Remote Work: ORA_ON_SITE Description The Data Scientist will apply their technical and analytical capabilities to support key business and security objectives. This ...

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Remote Nhl Data Analytics information

Do NFL teams hire data analysts?

Yes, NFL teams hire data analysts to evaluate player performance, game strategies, and team statistics. These analysts often use data visualization tools and statistical software to support decision-making and improve team outcomes.

What are Remote NHL Data Analytics jobs?

Remote NHL Data Analytics jobs involve analyzing hockey-related data for the National Hockey League (NHL) while working from a remote location. Professionals in this field collect, organize, and interpret large datasets to provide insights into player performance, team strategies, and game outcomes. The work may include statistical modeling, data visualization, and the use of specialized software to help teams, media, or betting companies make informed decisions. These positions typically require strong analytical skills, proficiency in programming languages like Python or R, and a deep understanding of hockey. Remote roles allow for flexibility in location while still collaborating with teams and organizations virtually.

What are some common challenges faced by professionals in a Remote NHL Data Analytics role, and how can they be addressed?

A common challenge in remote NHL Data Analytics is ensuring seamless collaboration with coaches, scouts, and other analysts despite being physically distant from the team. Clear communication and regular virtual meetings are essential to align on objectives and share insights. Another challenge is managing and accessing large, proprietary datasets securely from remote locations, which requires strong data management practices and familiarity with secure cloud platforms. Staying updated on the latest hockey analytics trends and tools is also important for delivering actionable insights to the team.

What is the difference between Remote Nhl Data Analytics vs Remote Sports Data Analyst?

AspectRemote Nhl Data AnalyticsRemote Sports Data Analyst
CredentialsDegree in Data Science, Statistics, or Sports ManagementDegree in Data Science, Statistics, or Sports Management
Work EnvironmentRemote, sports analytics companies, NHL teamsRemote, sports organizations, analytics firms
Industry UsagePrimarily NHL, hockey-focused analyticsVarious sports including hockey, football, basketball
Job FocusHockey-specific data analysis, player performance, game strategiesMultiple sports data analysis, performance metrics, trend forecasting

Remote Nhl Data Analytics specializes in hockey-specific data analysis within the NHL industry, focusing on player performance and game strategies. In contrast, Remote Sports Data Analyst roles cover multiple sports, analyzing broader performance metrics across various leagues. Both roles require similar credentials and often share work environments, but their industry focus and data scope differ significantly.

How much do NHL data analysts make?

NHL data analysts typically earn between $50,000 and $80,000 annually, depending on experience, education, and the organization. Advanced skills in data analysis tools and sports statistics can lead to higher salaries in this specialized field.

What are the key skills and qualifications needed to thrive as a Remote NHL Data Analyst, and why are they important?

To thrive as a Remote NHL Data Analyst, you need a strong foundation in statistics, data analysis, and hockey knowledge, typically supported by a degree in data science, statistics, or a related field. Familiarity with analytics tools like Python, R, SQL, and visualization platforms such as Tableau or Power BI is essential, along with experience using sports data sources and APIs. Excellent problem-solving, communication, and self-motivation are crucial soft skills for collaborating with remote teams and conveying insights to stakeholders. These skills and qualities are important for producing accurate, actionable insights that drive team strategy and performance improvements in a fast-paced, competitive sports environment.

Is it possible to get a remote job as a data analyst?

Yes, remote data analyst positions are widely available across various industries, including sports analytics like NHL data analysis. These roles typically require skills in data visualization, statistical analysis, and tools such as Excel, SQL, or Python, and often offer flexible schedules. Many companies and organizations now hire remote data analysts, making it a feasible career option for qualified candidates.

How to become an NHL data analyst?

To become an NHL data analyst, candidates typically need a strong background in statistics, data analysis, or related fields, often holding a bachelor's degree in mathematics, statistics, or sports management. Proficiency in data tools such as Excel, SQL, and programming languages like Python or R is essential, along with knowledge of hockey and sports analytics. Gaining experience through internships or projects related to sports data can improve job prospects in this specialized field.
What cities in Virginia are hiring for Remote Nhl Data Analytics jobs? Cities in Virginia with the most Remote Nhl Data Analytics job openings:
Infographic showing various Remote Nhl Data Analytics job openings in Virginia as of July 2026, with employment types broken down into 91% Full Time, 6% Part Time, and 3% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution.
Manager, Data Analytics - Remote

Manager, Data Analytics - Remote

ICF International, Inc.

Reston, VA โ€ข On-site, Remote

Full-time

Posted 9 days ago


Job description

This role is contingent upon a contract award.
ICF is seeking an experienced Data Analytics Manager to lead enterprise data, analytics, governance, and AI-enabled capabilities for a complex federal technology services program. This role will support the design, implementation, and sustainment of data policy, standards, governance processes, portfolio management practices, data architecture, data quality controls, analytics products, dashboards, and secure data access models.
The ideal candidate has demonstrated experience leading enterprise data initiatives in regulated environments, with strong technical credibility across data governance, data architecture, data engineering, analytics, data quality, metadata management, and responsible AI-enabled analytics. This role requires the ability to translate business, operational, and mission needs into governed, secure, and usable data capabilities that support decision-making, performance management, and continuous improvement.
Job Location: This position is remote within the United States.
Please note that ICF monitors employee work locations, restricts access from foreign locations and IP addresses, and prohibits the use of personal VPN connections.
What You'll Be Doing
  • Lead enterprise data, analytics, governance, and AI-enabled capability delivery across a complex federal technology environment.
  • Develop and implement data governance policies, standards, operating procedures, approval workflows, and accountability models.
  • Establish and maintain data portfolio management practices, including prioritization, project intake, resource planning, risk tracking, milestone reporting, and performance measurement.
  • Lead the design and implementation of scalable data architecture, including data pipelines, data lakes, data warehouses, data marts, data catalogs, metadata repositories, and data lineage capabilities.
  • Define and enforce data quality standards, validation rules, data dictionaries, scorecards, issue management workflows, and continuous monitoring processes.
  • Guide development of analytics products, dashboards, reports, and visualization tools that provide operational insight and support executive decision-making.
  • Support advanced analytics capabilities, including statistical analysis, predictive modeling, trend analysis, root cause analysis, and AI-enabled analytics.
  • Ensure data sharing, API integration, and data access models are secure, governed, auditable, and aligned with privacy, cybersecurity, and compliance requirements.
  • Partner with cybersecurity, engineering, product, and program management teams to align data platforms, applications, integrations, and analytics capabilities with enterprise standards.
  • Establish reusable templates, frameworks, data models, ETL/ELT patterns, documentation repositories, and project management toolkits for data initiatives.
  • Support training, documentation, and knowledge transfer to improve user adoption and long-term sustainment of data tools, dashboards, and data management practices.
  • Monitor data quality, data usage, access patterns, and analytics adoption to identify risks, improvement opportunities, and operational blind spots.

What You Must Have
  • U.S. Citizenship required due to federal contract requirements.
  • Must be able to obtain and maintain a Federal Public Trust clearance.
  • Bachelor's Degree
  • 10+ years of experience leading enterprise data, analytics, data governance, data engineering, data architecture, or AI-enabled analytics initiatives.
  • One active data, cloud, analytics, AI/ML, or data governance certification, such as CDMP, DAMA, AWS/Azure/GCP data certification, Microsoft Power BI certification, Databricks, Snowflake, or equivalent

What we would like you to have:
  • 8+ years of experience designing, implementing, or managing enterprise data platforms, data pipelines, data warehouses, data lakes, data marts, data catalogs, or metadata management capabilities.
  • 5+ years of experience establishing data governance policies, standards, stewardship models, data quality frameworks, data dictionaries, lineage practices, or data management operating models.
  • 5+ years of experience delivering analytics products, dashboards, reporting capabilities, data visualizations, or executive decision-support tools.
  • 5+ years of experience working in federal, public sector, healthcare, life sciences, or other regulated environments with formal privacy, security, or compliance requirements.
  • 3+ years of experience supporting AI-enabled analytics, predictive modeling, machine learning workflows, anomaly detection, or advanced analytics use cases.
  • 3+ years of experience with data integration methods, including APIs, ETL/ELT pipelines, data orchestration, batch processing, real-time ingestion, or change data capture.
  • 3+ years of experience using data visualization, analytics, or business intelligence tools such as Power BI, Tableau, QuickSight, Looker, Palantir Foundry, or similar platforms.
  • 3+ years of experience with cloud data services on AWS, Microsoft Azure, Google Cloud Platform, or similar cloud environments.
  • Experience supporting HHS, NIH, FDA, CMS, CDC, or other health-focused federal environments.
  • Experience building or supporting Chief Data Office functions, enterprise data governance programs, or data portfolio management organizations.
  • Experience with data privacy, data protection, data classification, DLP, encryption, RBAC, ABAC, just-in-time access, or audit logging requirements.
  • Experience aligning data capabilities with NIST, FISMA, HIPAA, FedRAMP, GDPR, or other security and compliance frameworks.
  • Experience developing data catalogs, metadata management approaches, lineage models, data quality scorecards, data issue repositories, and data stewardship workflows.
  • Experience implementing AI governance, responsible AI practices, model monitoring, explainability, human-in-the-loop review, or secure AI-enabled analytics.
  • Experience with SQL, Python, R, Databricks, Snowflake, Redshift, BigQuery, Synapse, Dataverse, or similar data platforms and tools.
  • Additional cloud, data, analytics, AI/ML, cybersecurity, Agile, ITIL, DAMA, CDMP, or project management certification.

Working at ICF
ICF is a global advisory and technology services provider, but we're not your typical consultants. We combine unmatched expertise with cutting-edge technology to help clients solve their most complex challenges, navigate change, and shape the future.
We can only solve the world's toughest challenges by building a workplace that allows everyone to thrive. We are an equal opportunity employer. Together, our employees are empowered to share their expertise and collaborate with others to achieve personal and professional goals. For more information, please read our EEO policy.
We will consider for employment qualified applicants with arrest and conviction records.
Reasonable Accommodations are available, including, but not limited to, for disabled veterans, individuals with disabilities, and individuals with sincerely held religious beliefs, in all phases of the application and employment process. To request an accommodation, please email Candidateaccommodation@icf.com and we will be happy to assist. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
Read more about workplace discrimination rights or our benefit offerings which are included in the Transparency in (Benefits) Coverage Act.
Candidate AI Usage Policy
At ICF, we are committed to ensuring a fair interview process for all candidates based on their own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) tools to generate or assist with responses during interviews (whether in-person or virtual) is not permitted. This policy is in place to maintain the integrity and authenticity of the interview process.
However, we understand that some candidates may require accommodation that involves the use of AI. If such an accommodation is needed, candidates are instructed to contact us in advance at candidateaccommodation@icf.com. We are dedicated to providing the necessary support to ensure that all candidates have an equal opportunity to succeed.
Pay Range - There are multiple factors that are considered in determining final pay for a position, including, but not limited to, relevant work experience, skills, certifications and competencies that align to the specified role, geographic location, education and certifications as well as contract provisions regarding labor categories that are specific to the position.
The pay range for this position based on full-time employment is:
$98,614.00 - $167,644.00
Nationwide Remote Office (US99)