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Predictive Modeling Sports Jobs (NOW HIRING)

Onyx Games LLC

Project Manager

New York, NY · On-site

Interest in sports analytics and predictive modeling is highly desirable Tools & Technologies * Project management tools (Jira, Asana, ClickUp, or similar) * Collaboration tools (Slack, Notion ...

Dime Line Trading

Quantitative Trader

Chicago, IL

Design, build, and maintain predictive models and trading strategies * Conduct independent ... Work evenings and weekends during active sports schedules Required Skills * 2-5+ years of ...

AEG

Sports Trading Analyst

San Francisco, CA · On-site

$70K - $120K/yr

We are looking for team-oriented individuals with an authentic passion for accurate, predictive ... Identify model discrepancies, edge cases, and structural inefficiencies in pricing workflows ...

Swish Analytics

Sports Data Analyst

San Francisco, CA · On-site +1

We're looking for team-oriented individuals with an authentic passion for accurate and predictive ... Production model feature deep dives to explain project market lines * Clearly document findings

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Predictive Modeling Sports information

How do predictive modeling sports professionals typically collaborate with coaches and analysts to improve team performance?

Predictive modeling sports professionals work closely with coaches and analysts by translating complex data patterns into actionable insights. They often participate in regular strategy meetings to present their findings, discuss trends, and suggest data-driven adjustments for training or game tactics. Effective communication and the ability to explain statistical concepts in practical terms are essential, as their analyses directly inform decision-making processes. This collaborative environment helps teams gain a competitive edge by leveraging data for continuous improvement.

What are the key skills and qualifications needed to thrive in Predictive Modeling for Sports, and why are they important?

To thrive in Predictive Modeling for Sports, you need a solid background in statistics, mathematics, and data analysis, often supported by a degree in a quantitative field. Familiarity with programming languages like Python or R, experience with machine learning frameworks, and knowledge of sports databases are typically required. Strong problem-solving, critical thinking, and effective communication skills help you interpret results and convey insights to stakeholders. These abilities are essential for developing accurate models, making informed predictions, and driving strategic decisions in sports organizations.

What is predictive modeling in sports?

Predictive modeling in sports involves using statistical techniques and data analysis to forecast outcomes of sporting events, player performance, or team success. Analysts use historical data, player statistics, and sometimes machine learning algorithms to build models that can predict future results. These models are widely used in sports betting, team management, and performance optimization. Their accuracy depends on the quality of data and the sophistication of the modeling techniques.
Infographic showing various Predictive Modeling Sports job openings in the United States as of May 2026, with employment types broken down into 2% As Needed, 56% Full Time, 38% Part Time, and 4% Temporary. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Director of Business Intelligence

Director of Business Intelligence

Pacers Sports & Entertainment

Indianapolis, IN • On-site

Full-time

Posted 3 days ago

Job description

SUMMARY
The Director of Business Intelligence will report to the AVP of Business Intelligence & MarTech. The Director of Business Intelligence serves as a strategic leader responsible for transforming data into meaningful insights that drive decision making across all Pacers Sports & Entertainment (PS&E) brands. This role blends strong technical expertise with exceptional business acumen to identify trends, uncover opportunities, and guide revenue-generating and efficiency enhancing initiatives.
The ideal candidate is equally comfortable architecting data models as they are presenting concise, actionable insights to executives. They will oversee the acquisition, governance, and enrichment of data assets, ensuring the organization leverages high quality, connected data to inform marketing, ticketing, partnerships, operations, and overall business performance. A key responsibility of this role is upholding data quality as a foundational priority and building trust in data across the organization.
This leader will proactively analyze complex datasets, distill key takeaways, and anticipate the needs of stakeholders across departments. They will champion a data-driven culture: empowering teams with dashboards, predictive models, and strategic recommendations that improve customer understanding, optimize performance, and maximize ROI.
ESSENTIAL DUTIES / RESPONSIBILITIES
  • Apply advanced data modeling, predictive analytics, and statistical techniques to uncover trends, interpret key findings, and translate insights into initiatives that drive measurable business outcomes.
  • Lead the development and deployment of data-driven solutions across the organization, ensuring insights are actionable and embedded into decision-making processes at all levels.
  • Design, build, and maintain enterprise dashboards and analytical reports that track KPIs, monitor performance, and evaluate the ROI of marketing, sales, partnerships, and operational strategies.
  • Own the organization's survey strategy, including the design, deployment, and optimization of surveys that capture customer, fan, partner, and prospect sentiment and behaviors.
  • Synthesize data into actionable insights, delivering clear visualizations and storytelling in strategic presentations that support executive decision-making and cross-department alignment.
  • Analyze full-funnel marketing performance and optimize campaign revenue tracking through direct and influenced revenue across email, SMS, social ads and more to evaluate channel effectiveness, guide optimization decisions and audience curation, and enhance budget allocation strategies.
  • Perform market research and competitive analysis to identify macro trends, benchmark performance, and uncover new opportunities for revenue growth and fan engagement.
  • Lead audience research, predictive modeling, segmentation, and persona development to strengthen targeting, personalization, product strategy, and sponsorship storytelling.
  • Oversee, develop, and mentor analysts, fostering a culture of curiosity, analytical rigor, and continuous improvement within the BI team.
  • Champion data quality, acquisition, and governance, ensuring the organization consistently leverages clean, connected, and enriched data assets.
  • Collaborate cross-functionally with marketing, ticketing, partnerships, finance, operations, and product teams to identify analytical needs and maximize business impact.
  • Oversee target audience creation and net new ingestion and predictive modeling for the Retail Media Network as well as track outcomes and opportunity for growth.
  • Perform other duties and lead strategic projects as assigned.

QUALIFICATION REQUIREMENTS
To perform this job successfully, an individual must be able to perform each duty satisfactorily. The requirements listed above are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
EDUCATION and/or EXPERIENCE:
  • Bachelor's degree required, with strong preference for analytics, statistics, computer science, economics, or a related technical discipline.
  • 8+ years of experience in business intelligence, marketing analytics, sales analytics, or similar analytical role.
  • 5+ years of supervisory or team-lead experience, including coaching and developing analysts.
  • Exceptional communication skills, with the ability to translate complex analytical concepts for audiences of all technical levels.
  • Advanced SQL proficiency, including multi-table joins, subqueries, and performance-optimized querying.
  • Strong grounding in data mining and data engineering principles, including predictive analytics, data mapping, and integrating on-premises and cloud-based data sources.
  • Hands-on experience with statistical modeling techniques, such as GLM, logistic regression, variable selection, and other predictive methods.
  • Experience writing advanced SAS code, including complex models, macros, and automation workflows.
  • Proficiency with Qualtrics and experience integrating survey data into CRM systems to enrich customer profiles.
  • Technical competency with statistical tools (Excel, R, or similar) and data visualization platforms (Tableau, Power BI, or equivalent).
  • Demonstrated experience working collaboratively across diverse business units, such as marketing, sales, partnerships, finance, and operations.
  • Experience in sports or entertainment industries is a plus but not required.

PHYSICAL AND ENVIRONMENTAL DEMANDS:
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
While performing the duties of this job the employee is regularly required to:
  • Sit
  • Stand
  • Walk
  • Speak in public
  • Use telephone
  • Use computer
  • Speak, hear and write

WORK ENVIRONMENT:
The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
  • The noise level in the office work environment is usually moderate.
  • The noise level in Gainbridge Fieldhouse/game environment is usually loud.
  • The stress level may become high during certain times.

We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, age, gender identity, marital status, disability status, protected veteran status, or any other characteristic protected by law.

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