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Data Analytics Sports Jobs (NOW HIRING)

Swish Analytics

Trading Analyst

San Francisco, CA · On-site +1

Company Overview Swish Analytics is a sports analytics, betting, and fantasy startup building the next generation of predictive sports data products. We believe that oddsmaking is a challenge rooted ...

Swish Analytics

Trading Analyst

San Francisco, CA

Company Overview Swish Analytics is a sports analytics, betting, and fantasy startup building the next generation of predictive sports data products. We believe that oddsmaking is a challenge rooted ...

FanDuel

Campaign Analytics, Data Analyst

New York, NY · On-site

In this role you will be responsible for performance analytics, reporting and data analysis across ... If you would like to play a key role in an emerging US Sports Betting market opportunity, then this ...

FanDuel

Campaign Analytics, Data Analyst

New York, NY

In this role you will be responsible for performance analytics, reporting and data analysis across ... If you would like to play a key role in an emerging US Sports Betting market opportunity, then this ...

Versant Media

Sr. Data Analyst

Orlando, FL

$80K - $101K/yr

... sports division USA Sports, along with complementary digital assets including Fandango, Rotten ... Bachelor's degree is required in Business Analytics, Computer Information Systems, Industrial ...

BURLEBO

Data and Analytics Engineer

Austin, TX · On-site

They are seeking an experienced Data and Analytics Engineer to build and lead their data and ... Burlebo designs apparel for the modern sportsman, offering swim trunks, running shorts, and caps ...

Windquest

Sr Data Analyst - Crecera Brands

Minneapolis, MN · On-site

$75K - $110K/yr

Sr. Data Analyst ABOUT THE COMPANY Crecera Brands is the driving force behind Sportsman's Guide, Salt Strong, The Golfer's World, Play Baseball and Play Softball, five of America's leading retailers ...

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Data Analytics Sports information

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How much do data analytics sports jobs pay per year?

As of Jul 14, 2026, the average yearly pay for data analytics sports in the United States is $98,195.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,000.00 and $131,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Analytics Sports professional, and why are they important?

To thrive as a Data Analytics Sports professional, you need strong statistical analysis skills, a background in mathematics or data science, and familiarity with sports industry metrics. Proficiency with data visualization tools (like Tableau), programming languages (such as Python or R), and sports analytics software is typically required. Analytical thinking, attention to detail, and strong communication skills set top performers apart in this field. These skills are crucial for transforming complex data into actionable insights that enhance team performance and inform strategic sports decisions.

What are some common challenges faced by data analysts in the sports industry, and how can they be addressed?

Data analysts in the sports industry often encounter challenges such as integrating disparate data sources (e.g., player stats, wearable tech, and video analysis), ensuring data accuracy, and translating findings into actionable insights for coaches and management. Addressing these challenges requires strong technical skills, effective communication, and a collaborative approach with IT, coaching staff, and sports scientists. Staying updated with the latest analytics tools and maintaining clear documentation can also help streamline workflows and improve decision-making across teams.

What is the difference between Data Analytics Sports vs Data Analysis in Finance?

AspectData Analytics SportsData Analysis in Finance
Required CredentialsBachelor's in Sports Management, Data Science, or related fields; certifications like SAS or TableauBachelor's in Finance, Economics, or related fields; certifications like CFA, CPA
Work EnvironmentSports teams, leagues, sports analytics firms, media companiesBanks, investment firms, financial institutions, corporate finance departments
Employer & Industry UsageUsed to improve team performance, player stats, fan engagementUsed for risk assessment, investment decisions, financial forecasting

Data Analytics Sports focuses on analyzing sports-related data to enhance team performance and fan engagement, while Data Analysis in Finance centers on financial data to inform investment and business decisions. Both roles require strong analytical skills and data tools but serve different industries and objectives.

What are data analytics sports jobs?

Data analytics sports jobs involve using data analysis techniques to help sports teams, organizations, or media companies make better decisions. Professionals in this field collect, process, and interpret data related to player performance, game strategy, fan engagement, and business operations. They use statistical tools, programming languages, and visualization software to turn raw data into actionable insights. These roles are vital for gaining a competitive edge, optimizing team performance, and enhancing fan experiences in the sports industry.
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Data Analytics Sports jobs near you
Trading Analyst

Trading Analyst

Swish Analytics

San Francisco, CA • On-site, Remote

Full-time

Re-posted 16 days ago

Job description

Company Overview
Swish Analytics is a sports analytics, betting, and fantasy startup building the next generation of predictive sports data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports expertise, not intuition. We are looking for team-oriented individuals with an authentic passion for accurate, predictive, real-time data who can execute in a fast-paced, creative, and continually evolving environment without sacrificing technical excellence.
Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building high-performance pricing and trading systems.
Job Description
Swish is looking for a highly analytical Sports Trading Analyst to help strengthen and scale our sports pricing and trading operation.
In this role, you will work at the intersection of sports intelligence, quantitative modelling, pricing strategy, and live market behaviour. You will help manage and improve real-time pricing across a range of sports and market types, with a particular focus on market aware price discovery, risk management and the identification of actionable trading signals from market activity.
This role is suited to someone with strong quantitative reasoning, excellent decision-making under pressure, and a deep interest in how markets are formed, odds move, and how to engineer accurate pricing in the competitive sports betting environment.
You will work in a geographically dispersed team alongside experienced traders, quants, data scientists, and engineers, with colleagues based across Europe and the US.
Duties
  • Monitor live sports markets and market activity in real time across a range of sports and market types
  • Support the calibration and refinement of prices using market signals, statistical models, competitor benchmarking, and event-driven information
  • Help improve pricing quality through the analysis of market behaviour, price sensitivity, liquidity patterns, and reaction speed to new information
  • Contribute to the development, testing, and refinement of quantitative models by applying your understanding of live market dynamics and pricing behaviour
  • Own and manage real-time trading risk, including exposure monitoring, liability controls, and disciplined decision-making across concurrent events
  • Collaborate with engineering on trading and pricing infrastructure, including API integrations, automated monitoring, alerting, anomaly detection, and execution tooling
  • Work closely with Sports Trading teams to interpret breaking news, lineups, injuries, team news, and other event-specific developments to ensure timely and accurate price updates
  • Identify model discrepancies, edge cases, and structural inefficiencies in pricing workflows, escalating and documenting findings for Data Science and Data Engineering teams
  • Help evaluate market opportunities, prioritise resources across sports and competitions, and improve operational processes as the trading function scales
  • Detect sharp or informative market activity and ensure useful signals are fed back into Swish's proprietary models and pricing systems
  • Communicate effectively with internal Sports Trading teams responsible for maintaining and improving our core sportsbook pricing models
Requirements
  • Bachelor's degree or higher in a quantitative or analytical discipline (Mathematics, Statistics, Computer Science, Economics, Engineering, Quantitative Finance, or similar), or equivalent practical experience
  • Strong grounding in probability, statistics, and expected value, with the ability to reason clearly about fair price, uncertainty, and risk
  • Hands-on experience in sports trading, sports betting, exchange-style environments, market-making, quantitative trading, or other closely related domains where fast price formation and disciplined execution matter
  • Strong understanding of sports betting fundamentals, including odds formats (decimal, fractional, American), implied probability conversion, expected value, and closing line value
  • Demonstrated ability to make high-quality decisions under time pressure with incomplete information during live events
  • Comfortable working autonomously across global event schedules, including weekends and major tournament periods
  • Fluent in English, written and spoken, with clear communication skills in a distributed and asynchronous team environment
Preferred (but not essential)
  • Track record of building and backtesting quantitative models using real historical data; GitHub, notebooks, or demonstrable analytical work is highly valued
  • Deep domain knowledge across high-turnover sporting verticals such as NBA, NFL, and Soccer
  • Understanding of relational database systems (MySQL or equivalent) for analysis of prices, outcomes, and trading decisions
  • Familiarity with market microstructure concepts such as adverse selection, inventory risk, liquidity dynamics, queue positioning, or execution quality
  • Experience using Python for quantitative research, exploratory data analysis, prototyping, or model improvement
  • Experience using modern AI tools to accelerate analysis, research, and modelling workflows
Why Join
This is an opportunity to play a meaningful role in a growing and well-resourced sports trading operation. The successful candidate will help shape process, tooling, and decision-making within a team focused on high-quality pricing, efficient execution, and long-term product excellence across multiple sports verticals.
Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer's discretion, this position may require successful completion of background and reference checks.
Department Trading Operations Locations San Francisco, CA - Remote, Malta - Remote, Spain - Remote, United Kingdom - Remote Remote status Fully Remote

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