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Aws Sports Analytics Jobs (NOW HIRING)

SumerSports LLC

AI Application Engineer

Explore how LLMs, retrieval, and deterministic logic can create novel sports analytics tools. Use ... Experience deploying on Vercel, AWS, or GCP with modern CI/CD. * Comfortable working in a pod-based ...

Ursus, Inc.

MLOps/ML Platform Engineer

... cloud infrastructure (AWS, GCP, or Azure). • Hands-on experience managing GPU clusters and ... sports analytics or other high-volume data domains. • Experience integrating LLM workflows or ...

Amazon

Sr Financial Analyst, AWS Marketing Finance

Seattle, WA · On-site

$97K - $121K/yr

Amazon Web Services (AWS) Marketing Finance seeks a Senior Financial Analyst to serve as a finance ... sports marketing, and product marketing. You will own the financial narrative for your business ...

SumerSports LLC

MLOps / ML Platform Engineer

Deep knowledge of Kubernetes, CI/CD, containers, and cloud infrastructure (AWS, GCP, or Azure ... Background in sports analytics or other high-volume data domains. * Experience integrating LLM ...

TicketManager

Data & Analytics Lead

Calabasas, CA · On-site

$80K - $100K/yr

We're also proud to partner with some of the most iconic teams and venues in sports and ... You will manage our Data Lake (AWS or Azure), scale our Power BI Fabric implementation, and act as ...

AEG

Data Engineer

Pittsburgh, PA · On-site

$111K - $133K/yr

Equivalent experience in AWS or Azure is acceptable, but GCP is our primary environment ... Exposure to cutting-edge work in agentic AI applied to sports analytics. * A team culture that ...

Amazon

Sr Financial Analyst, AWS Marketing Finance

Seattle, WA · On-site

$97K - $121K/yr

Amazon Web Services (AWS) Marketing Finance seeks a Senior Financial Analyst to serve as a finance ... sports marketing, and product marketing. You will own the financial narrative for your business ...

SumerSports LLC

LLMOps Platform Engineer

Experience deploying models or AI systems in production environments (AWS, GCP, or Azure ... Background in sports analytics, data engineering, or multimodal (video/text) systems. * Exposure to ...

TicketManager

Data & Analytics Lead

Calabasas, CA · On-site

$80K - $100K/yr

We're also proud to partner with some of the most iconic teams and venues in sports and ... You will manage our Data Lake (AWS or Azure), scale our Power BI Fabric implementation, and act as ...

AEG

Data & Analytics Lead

Calabasas, CA · On-site

We're also proud to partner with some of the most iconic teams and venues in sports and ... You will manage our Data Lake (AWS or Azure), scale our Power BI Fabric implementation, and act as ...

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$136.2K

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How much do aws sports analytics jobs pay per year?

As of Jun 11, 2026, the average yearly pay for aws sports analytics in the United States is $136,232.00, according to ZipRecruiter salary data. Most workers in this role earn between $128,000.00 and $144,500.00 per year, depending on experience, location, and employer.

Do sports analysts make good money?

Sports analysts can earn a wide range of salaries depending on their experience, employer, and level of expertise. Entry-level positions may pay modestly, while experienced analysts working for major sports networks or teams can earn six-figure incomes. Skills in data analysis, statistics, and familiarity with sports-specific tools can influence earning potential.

What kind of job can you get with a sports analytics degree?

A sports analytics degree can lead to roles such as sports analyst, data analyst, or performance analyst, where professionals analyze player and team data to inform strategies. These jobs often require skills in statistical software, data visualization, and knowledge of sports metrics, with opportunities in professional teams, sports organizations, or media companies.

Are sports analytics jobs in demand?

Sports analytics jobs are increasingly in demand as teams and organizations seek data-driven insights to improve performance and decision-making. Professionals in this field often need skills in data analysis, statistics, and familiarity with tools like R or Python, with opportunities growing across professional and collegiate sports sectors.

What are the key skills and qualifications needed to thrive in the Aws Sports Analytics position, and why are they important?

To excel in AWS Sports Analytics, you need expertise in data analysis, statistics, and a solid understanding of cloud computing, often supported by a degree in data science, computer science, or a related field. Proficiency with AWS services (such as S3, Redshift, and SageMaker), data visualization tools like Tableau or Power BI, and relevant certifications like AWS Certified Data Analytics are highly valuable. Strong communication, problem-solving skills, and the ability to collaborate effectively with cross-functional teams are essential soft skills. These competencies ensure you can deliver actionable sports insights, architect scalable solutions, and support data-driven decision-making in high-performance environments.

What is an AWS Sports Analytics job?

An AWS Sports Analytics job involves leveraging Amazon Web Services (AWS) to analyze sports data for performance insights, strategy optimization, and decision-making. Professionals in this role use cloud-based tools like AWS Glue, Lambda, SageMaker, and Redshift to process and visualize large datasets from games, athletes, and teams. They work with machine learning models, real-time analytics, and data pipelines to improve team performance, fan engagement, and business operations. This role requires expertise in data engineering, statistics, and cloud computing to turn raw sports data into actionable insights.

What are some common day-to-day responsibilities for professionals working in AWS Sports Analytics roles?

In AWS Sports Analytics positions, you'll typically be responsible for collecting, cleaning, and analyzing large volumes of sports data using cloud-based tools. You may build or maintain machine learning models to predict player performance, optimize team strategies, or enhance fan engagement. Collaboration is frequent, as you'll work closely with data engineers, coaches, and stakeholders to translate data insights into actionable recommendations. The work environment is often fast-paced, requiring adaptability, attention to detail, and continuous learning to keep up with technological advancements and evolving sports analytics needs.

What AWS jobs are in high demand?

In the field of AWS sports analytics, roles such as AWS Data Engineer, Cloud Solutions Architect, and Data Scientist are in high demand due to the need for cloud infrastructure management, data processing, and analytics expertise. These positions often require skills in AWS services like S3, Lambda, and Redshift, along with knowledge of data modeling and programming languages such as Python or SQL.
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Aws Sports Analytics jobs near you
Senior Quantitative Researcher - Market Microstructure

Senior Quantitative Researcher - Market Microstructure

Swish Analytics

San Francisco, CA • On-site, Remote

$165K - $200K/yr

Full-time

Posted 27 days ago

Job description

Company Description
Swish Analytics is a sports analytics, betting, and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and 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 systems to support products across a variety of industries and consumer/enterprise clients.
As we expand our presence on betting exchanges, we're building infrastructure and strategies akin to those found in traditional financial markets. Our challenges are unique, and we hope you're comfortable in uncharted territory.
Role Overview
As a Senior Quantitative Researcher, you will own end-to-end research and production pipelines for one or more trading strategies. You'll lead research initiatives that generate alpha and improve execution quality, mentor junior researchers, and collaborate closely with our Trading desk to translate quantitative insights into profitable systematic strategies while maintaining rigorous risk management.
Core Responsibilities
  • Own end-to-end research and production pipelines for a strategy
  • Lead alpha research initiatives leveraging advanced statistical and machine learning techniques
  • Process and analyze high-frequency tick data, order book snapshots, and market microstructure signals with sub-millisecond latency requirements
  • Analyze price formation, market liquidity dynamics, and limit order book imbalances across electronic venues
  • Build and run Monte Carlo simulations to estimate P&L distributions, risk exposures, and portfolio dynamics
  • Develop, backtest, and optimize quantitative trading strategies with rigorous statistical validation
  • Interpret complex model outputs and communicate alpha generation mechanisms to portfolio managers
  • Write modular, clean, and efficient Python code; build custom analytics libraries and research frameworks
  • Lead design reviews and establish data quality and research reproducibility standards
  • Guide 1-2 junior researchers through project delivery and model development
  • Proactively engage with traders and infrastructure teams to clarify research objectives and resolve data dependencies

Execution & Market Microstructure
  • Design and implement transaction cost analysis (TCA) frameworks to measure and improve execution quality
  • Build market impact models and optimal execution strategies to minimize slippage across venue types
  • Develop real-time monitoring systems for latency, adverse selection, and execution performance metrics
  • Partner with infrastructure teams on ultra-low-latency data feeds and smart order routing algorithms

Requirements:
  • Master's degree in a quantitative discipline (Mathematics, Statistics, Physics, Computer Science, Financial Engineering) strongly preferred; PhD a plus
  • Expert-level Python skills; able to build production-grade research and trading systems
  • Strong SQL skills; experience with complex queries on tick databases and time-series datasets
  • Deep experience with Monte Carlo methods, stochastic calculus, and probabilistic modeling
  • Proven ability to develop, backtest, and deploy systematic trading strategies with demonstrable P&L
  • Experience processing high-frequency tick data and real-time market feeds
  • Familiarity with AWS or similar cloud infrastructure for large-scale backtesting and research
  • Track record of mentoring junior quantitative researchers
  • Excellent communication skills; ability to present complex quantitative research to portfolio managers and trading desks
  • Deep understanding of equity/futures market microstructure, order types, and matching engine logic
  • Experience building sophisticated TCA frameworks with market impact decomposition
  • Familiarity with FPGA or kernel-bypass networking for latency-critical applications
  • Minimum of 5 years of experience in quantitative research, systematic trading, or statistical modeling

Nice to Have
  • Proficiency in Rust, C++, or other systems languages for performance-critical components
  • Experience with MLOps, model monitoring, and adaptive retraining pipelines for regime detection
  • Background in derivatives pricing, options market making, or volatility arbitrage
  • Familiarity with FIX protocol, Betfair or Matchbook API experience, and ultra-low-latency trading infrastructure

Base salary: $165,000 - 200,000 + Bonus Plan
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 Analytics Role Trading Data Science Locations San Francisco, CA - Remote Remote status Fully Remote

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