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Nba Data Analytics Jobs in Texas (NOW HIRING)

Pega NBA Developer

Dallas, TX · On-site

$52 - $68/hr

Job Title: Pega NBA Developer Work Location: Dallas, TX Duration: 6+ Months Job Summary: We are ... The role focuses on delivering personalized, real-time customer experiences using data, analytics ...

Data Scientist - AI Enabled Call Center Efficiency and CEX Location- Hybrid, Jersey City, NJ Salary ... The ideal candidate will be equally comfortable with analytics and execution, owning the full NBA ...

Data Scientist - AI Enabled Call Center Efficiency and CEX Location- Hybrid, Jersey City, NJ Salary ... The ideal candidate will be equally comfortable with analytics and execution, owning the full NBA ...

Pega CDH Developer

Dallas, TX · On-site

$55.75 - $73/hr

... NBA Designer, and Customer Profile Designer. * Experience with Pega 8.x or higher versions. * Familiarity with data flows, adaptive models, and predictive analytics. * Experience in SQL queries

From specialty concept stores for the NBA and NHL to iconic clubhouse destinations for the Yankees ... This role leverages advanced data analytics and surveillance technology to detect fraud, while ...

Technical Product Manager

Plano, TX

$156K - $180K/yr

As a Product Manager in AE NBA Photon , you are an integral part of the team that innovates new ... Advanced knowledge of the product development life cycle, design, and data analytics * Proven ...

Technical Product Manager

Plano, TX · On-site

$156K - $180K/yr

As a Product Manager in AE NBA Photon , you are an integral part of the team that innovates new ... Advanced knowledge of the product development life cycle, design, and data analytics * Proven ...

Technical Product Manager

Plano, TX · On-site

$156K - $180K/yr

As a Product Manager in AE NBA Photon , you are an integral part of the team that innovates new ... Advanced knowledge of the product development life cycle, design, and data analytics * Proven ...

... NBA) and the Dallas Stars (NHL) . From championship games and sold-out concerts to world-class ... data prior to distribution. * Compile financial reports, analyze trends, and provide actionable ...

... NBA) and the Dallas Stars (NHL) . From championship games and sold-out concerts to world-class ... data prior to distribution. * Compile financial reports, analyze trends, and provide actionable ...

... NBA) and the Dallas Stars (NHL) . From championship games and sold-out concerts to world-class ... data prior to distribution. * Compile financial reports, analyze trends, and provide actionable ...

... data analysis, etc.) • Must be technologically savvy with propensity for understanding new ... S. broadcasts of MLB, NBA, and NHL games; and influences sports fans of all ages through the ...

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Nba Data Analytics information

What is NBA data analytics?

NBA data analytics involves the collection, processing, and interpretation of basketball-related data to support decision-making within NBA organizations. Analysts use statistics, machine learning, and data visualization to evaluate player performance, optimize team strategies, and gain competitive advantages. This field combines knowledge of basketball with technical skills in data science and often supports front office staff, coaches, and scouting departments. The insights from data analytics can influence player recruitment, game tactics, and injury prevention.

How much do NBA data analysts make?

NBA data analysts typically earn between $60,000 and $120,000 annually, depending on experience, education, and the level of responsibility. Entry-level analysts may start at lower salaries, while those with advanced skills in data visualization, statistical analysis, and familiarity with tools like SQL or Python can command higher pay.

How does an NBA Data Analytics professional typically collaborate with coaches and front office staff to influence team strategies?

NBA Data Analytics professionals play a crucial role in bridging the gap between raw data and actionable insights for coaches and front office staff. They regularly present their findings in clear, digestible formats—such as dashboards or reports—during team meetings or strategy sessions. Close collaboration is essential, as analysts often work alongside coaches to interpret player performance metrics, suggest lineup optimizations, or evaluate potential trades. This dynamic environment requires strong communication skills and the ability to translate complex analytics into practical recommendations that fit the team's goals and style of play.

How to become an NBA data analyst?

To become an NBA data analyst, you typically need a bachelor's degree in statistics, data science, or a related field, along with strong skills in data analysis tools like Excel, SQL, and programming languages such as Python or R. Experience with sports analytics, understanding of basketball metrics, and familiarity with visualization software like Tableau are also valuable. Gaining internships or entry-level positions in sports organizations can help build relevant experience and industry knowledge.

What are the key skills and qualifications needed to thrive as an NBA Data Analyst, and why are they important?

To thrive as an NBA Data Analyst, you need strong quantitative skills, a background in statistics or data science, and a solid understanding of basketball analytics. Proficiency in programming languages like Python or R, data visualization tools such as Tableau, and experience working with large sports datasets are typically required, along with knowledge of advanced analytics techniques. Excellent communication, critical thinking, and teamwork skills help analysts translate complex data into actionable insights for coaches and management. These skills are crucial for making data-driven decisions that can impact player performance, game strategy, and overall team success.

What does a data analyst do in the NBA?

An NBA data analyst collects, processes, and interprets basketball data to provide insights on player performance, team strategies, and game trends. They use statistical tools and software to support decision-making for coaching staff and management, often working with large datasets and advanced analytics techniques.

What is the difference between Nba Data Analytics vs Nba Video Analyst?

AspectNba Data AnalyticsNba Video Analyst
Required SkillsData analysis, statistical tools, programming (Python, R)Video editing, playback software, basketball knowledge
Work EnvironmentOffice, data centers, sports analytics firmsStadiums, training facilities, broadcast rooms
Industry UsagePlayer performance, game strategy, scoutingGame breakdowns, player tendencies, coaching support

While both roles support NBA teams, Nba Data Analytics focuses on analyzing numerical data to inform decisions, whereas Nba Video Analysts interpret game footage to provide visual insights. Both are essential but serve different functions within team operations.

How much do NBA analysts make?

NBA data analysts typically earn between $50,000 and $100,000 annually, depending on experience, education, and the level of the organization. Senior analysts or those working for major teams or leagues can earn higher salaries, often exceeding $100,000. Skills in data visualization, statistical software, and sports analytics are important for higher earning potential.
What cities in Texas are hiring for Nba Data Analytics jobs? Cities in Texas with the most Nba Data Analytics job openings:
Infographic showing various Nba Data Analytics job openings in Texas as of July 2026, with employment types broken down into 91% Full Time, 7% Part Time, and 2% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution.

$52 - $68/hr

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

Job Title: Pega NBA Developer
Work Location: Dallas, TX
Duration: 6+ Months
Job Summary:
We are looking for a Pega NBA (Next-Best-Action) Developer to design, build, and optimize decisioning and customer engagement solutions using Pega Customer Decision Hub (CDH). The role focuses on delivering personalized, real-time customer experiences using data, analytics, and AI-driven decision strategies.