1

Sport Data Analyst Jobs in Reston, VA (NOW HIRING)

Gastroenterologist

Fairfax, VA ยท On-site

$350K - $425K/yr

Access to nationwide data analytics * Opportunities in research and education * Ancillary revenue ... C. for museums, monuments, and professional sports * Close to Shenandoah Valley for hiking, camping ...

Access to nationwide data analytics * Opportunities in research and education * Ancillary revenue ... C. for museums, monuments, and professional sports * Close to Shenandoah Valley for hiking, camping ...

Gastroenterologist

Fairfax, VA ยท On-site

$350K - $425K/yr

Access to nationwide data analytics * Opportunities in research and education * Ancillary revenue ... C. for museums, monuments, and professional sports * Close to Shenandoah Valley for hiking, camping ...

Gastroenterologist

Fairfax, VA ยท On-site

$350K - $425K/yr

Access to nationwide data analytics * Opportunities in research and education * Ancillary revenue ... C. for museums, monuments, and professional sports * Close to Shenandoah Valley for hiking, camping ...

You are fluent in genomic data analysis at scale, comfortable with large genetic datasets, GWAS ... From regular Town Halls and team picnics to organised sports events, our social committee ensures ...

Showing results 41-60

Sport Data Analyst information

See Reston, VA salary details

$35.4K

$86K

$141.5K

How much do sport data analyst jobs pay per year?

As of Aug 7, 2026, the average yearly pay for sport data analyst in Reston, VA is $85,975.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,000.00 and $100,900.00 per year, depending on experience, location, and employer.

Can a sport data analyst become a sports analyst?

A sport data analyst can transition to a sports analyst role, as both positions involve analyzing sports data and providing insights. However, a sports analyst may focus more on broader performance analysis, commentary, or scouting, often requiring strong communication skills and industry knowledge. Gaining experience in presentation, reporting, and understanding game strategies can facilitate this career shift.

How much do sport data analysts get paid?

Sport data analysts typically earn between $50,000 and $80,000 annually, with salaries increasing with experience, education, and technical skills such as proficiency in data analysis tools and programming languages. Entry-level positions may start around $40,000, while experienced analysts or those working with professional teams can earn over $100,000 per year.

What does a sport data analyst do?

As a sports data analyst, your job is to collect and monitor the statistics for an athlete, game, or team. As part of this analysis, you may use an algorithm to help predict future performance, help apply the information to business decisions, or provide stats and feedback for announcers to mention during a game. Sports data analyst roles fall into two positions. The first is the business aspect. In this version of the job, your main role is helping improve the team's performance by applying data. In the second position, you focus more on entertainment and providing data to fans who want to know more about the athletes. This is a more time-sensitive job during games, and most sports data analysts spend hours inputting and evaluating information so they can be ready to answer questions.

What are the key skills and qualifications needed to thrive as a sport data analyst?

To thrive as a Sport Data Analyst, you need strong analytical skills, proficiency in statistics, and a relevant degree such as mathematics, data science, or sports analytics. Familiarity with data analysis tools like SQL, Python, R, and sports-specific software, as well as experience with data visualization platforms, is often required. Excellent communication, attention to detail, and the ability to work collaboratively with coaches and athletes are standout soft skills. These competencies are crucial for translating complex data into actionable insights that improve team performance and strategic decision-making.

What is the difference between Sport Data Analyst vs Sports Statistician?

AspectSport Data AnalystSports Statistician
Required CredentialsBachelor's in Sports Management, Data Science, or related fields; proficiency in data analysis toolsBachelor's or higher in Statistics, Mathematics, or related fields; strong analytical skills
Work EnvironmentSports teams, analytics firms, media companies, or sports organizationsResearch institutions, sports organizations, or media outlets
Employer & Industry UsageUsed for performance analysis, player evaluation, and strategic decision-makingUsed for statistical modeling, historical data analysis, and record keeping

While both roles involve analyzing sports data, Sport Data Analysts focus on applying data insights to improve team performance and strategy using advanced tools. Sports Statisticians primarily handle data collection, record-keeping, and statistical modeling. The roles often overlap but differ in their primary focus and application within the sports industry.

How does a sport data analyst typically collaborate with coaches and athletes to improve team performance?

Sport Data Analysts work closely with coaches and athletes to translate complex data into actionable insights that enhance performance. They often attend training sessions and matches to collect real-time data, and then meet with coaching staff to discuss trends, strengths, and areas for improvement. Effective communication is crucial, as analysts must present their findings in an understandable way that can directly inform game strategies, player development, and injury prevention. This collaborative environment fosters a cycle of continuous feedback and data-driven decision making.
What cities near Reston, VA are hiring for Sport Data Analyst jobs? Cities near Reston, VA with the most Sport Data Analyst job openings:
Infographic showing various Sport Data Analyst job openings in Reston, VA as of July 2026, with employment types broken down into 84% Full Time, and 16% Part Time. Highlights an 89% In-person, 5% Hybrid, and 6% Remote job distribution, with an average salary of $85,975 per year, or $41.3 per hour.

Senior AI/ML Developer with Security Clearance

Aperio Global

Mclean, VA โ€ข On-site

$56 - $73.75/hr

Other

Re-posted 21 days ago


Job description

Send your Resume to: How We're Different We believe the highest-impact work in national security and technology is a team sport. At Aperio Global, we operate as a single, cohesive force aligned on a handful of mission-critical efforts where our work truly moves the needle. We don't chase small wins. We solve for next. We view the intersection of cybersecurity, artificial intelligence, and data analytics as an empirical discipline as rigorous and consequential as any field in science or engineering. That means we bring intellectual honesty, accountability, and transparency to every problem we take on. Our team includes tech innovators, Intelligence Community veterans, and security professionals who know that the best solutions come from diverse minds working toward a common mission. We value our people, those working quietly behind the scenes, doing the hard work that keeps our nation secure. The best way to understand how we think is to see what we've built. From full-spectrum cyber operations and de-biased AI platforms to quantum networking and cloud-native software systems, our work speaks for itself. Come solve with us! Aperio Global is looking for a Senior AI/ML Developer to join an R&D team in McLean, VA focused on prototyping and evaluating emerging AI technologies. This is a hands-on engineering role in a fast-paced, experimentation-driven environment where you'll design, build, and iterate on cutting-edge solutions using Retrieval-Augmented Generation (RAG), large language models (LLMs), and modern data infrastructure. You won't be maintaining legacy systems or sitting in status meetings. You'll be figuring out what works, documenting what doesn't, and helping shape how the team approaches complex technical challenges with AI. Key Responsibilities
Design, develop, and prototype solutions leveraging RAG architectures, LLMs, and emerging AI/ML technologies
Build and iterate on proof-of-concept applications to evaluate and demonstrate new AI capabilities
Design, develop, and integrate RESTful APIs to enable data retrieval and exchange across systems
Own data modeling, querying, and performance optimization in PostgreSQL for AI/ML contexts
Collaborate with researchers and engineers to evaluate approaches, document results, and recommend technical next steps
Share insights and findings to support team-wide knowledge growth in AI/ML advancements Minimum Qualifications
Active TS/SCI clearance with polygraph (required at time of application)
Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field; equivalent professional experience may substitute
8+ years of relevant technical experience in software engineering and AI/ML development
Expert-level Python programming skills applied to machine learning and NLP systems
Hands-on experience designing and implementing RAG pipelines and LLM-based solutions
Demonstrated experience with large language models (LLMs), including prompt engineering, model evaluation, and transformer architectures
Experience designing and integrating RESTful APIs for data exchange and system integration
Deep expertise with PostgreSQL including schema design, complex querying, and performance tuning
Cloud infrastructure experience on AWS, GCP, or Azure including deploying and testing AI prototypes. Preferred Qualifications
Experience with vector databases such as pgvector, Pinecone, Weaviate, or Chroma to support semantic search and AI/ML workflows
Familiarity with LLM orchestration frameworks such as LangChain, LlamaIndex, or Haystack
Background or interest in geospatial data, systems, or analytic tools (e.g., PostGIS, GDAL)
Experience developing or maintaining data pipelines, ETL workflows, or orchestration tools such as Airflow or Prefect
Familiarity with MLOps practices including model deployment, versioning, and monitoring
Background or interest in working with geospatial data, systems, or analytic tools.
Experience developing or maintaining data pipelines and utilizing vector databases to support AI/ML workflows. Salary range is dependent on experience level: 200k-240k The salary range for this role represents Aperioโ€™s good-faith estimate of compensation at the time of posting. Placement within the range is based on multiple factors, including but not limited to an individualโ€™s qualifications, relevant experience, education, certifications, technical skills, contract labor categories and/or rates, work location, market conditions, and business needs.