Sports Analytics

Sports Analytics Engineer Jobs

2 jobs found

4d ago

AI Engineer

Genius Sports Group New York, NY

New York, NY

4d ago

$170k - $200k/yr Full time Artificial Intelligence Data Analytics Data Pipeline

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Job Description

Genius Sports Group is seeking a skilled AI Engineer to join the Sports AI team in New York, with hybrid work arrangements that enable collaboration across our live-data and product-focused environments. You will help build the next generation of applied AI systems powering sports analysis, automation, and actionable insights, drawing from both live and historical data. This role offers a competitive salary range and the opportunity to influence how fans experience sports worldwide. Location: New York, NY (hybrid) • Salary: USD 170,000 - 200,000 per year

Responsibilities

Own applied AI work end-to-end, from data exploration and early prototypes through evaluation, production integration, and iteration
Develop and compose models, algorithms, and inference pipelines that convert sports data into structured events, predictions, insights, and confidence-aware outputs
Build models for events such as event detection and event likelihood estimation, fan interest projection, and automation of manual play-by-play collection
Work with messy, multimodal sports data from tracking systems, video and CV outputs, audio, commentary, text, and structured feeds, including imperfect labels and ambiguous real-world examples
Define metrics, evaluation datasets, and benchmarks to measure AI system quality and guide model, algorithm, and product decisions
Train, adapt, evaluate, and integrate ML models and AI components, including multi-step systems where model, algorithmic, and LLM/agent outputs are composed, validated, and refined
Design workflows that use human review or correction data to improve evaluation, model iteration, and production output quality where appropriate
Work closely with CV engineers on training pipelines, labeling workflows, and model deployment patterns
Partner with product, data platform, infrastructure, and systems engineers to integrate evaluated AI outputs into real-time sports products and automation workflows
Mentor junior teammates and contribute to team knowledge-sharing, reviews, and experiment design

Requirements

3+ years of experience building production ML, CV, or AI systems
Ability to translate ambiguous sports product goals into concrete ML tasks, including defining the prediction target, identifying the right data, measuring output quality, and shipping production-ready solutions
Hands-on production ML/AI experience, including constructing datasets, defining features and labels, training and deploying models, evaluating outputs empirically, and shipping AI system capabilities into production
Strong modeling judgment across deep learning and classical ML, with experience choosing approaches based on data inputs and problem structure
Experience with predictive modeling, event detection, data labeling, data quality improvement, and communicating experiment results to technical and non-technical stakeholders
Ability to evaluate AI system quality beyond anecdotal inspection, including reasoning about ambiguous outputs, imperfect labels, uncertainty, and real-world product tradeoffs
Strong production engineering fundamentals, including testing, observability, performance, and reliability
Demonstrated interest in the fast-moving landscape of LLMs, latest models, agentic AI systems, and development frameworks
Comfortable working in fast-moving, iterative environments with evolving requirements

Technologies

AWS Bedrock
Union
Rust
LLM APIs

Benefits

Benefits plan

About the Role

Genius Sports is enabling a new era of sports for fans worldwide by combining next-gen technology with live data to deliver experiences that are more immersive, interactive and personalized than ever before. We are looking for an AI Engineer on our Sports AI team to help build the next generation of applied AI systems powering sports analysis, automation, and insights.

Preferred Qualifications

Hands-on experience with LLM-integrated workflows, LLM APIs or cloud AI platforms such as AWS Bedrock, agentic AI systems, multi-agent systems, or evaluation of LLM/agent outputs in production workflows
Experience with ML/CV domains relevant to sports understanding, such as action recognition, sequence modeling, multimodal modeling, object detection, tracking, or player identification
Experience working with player tracking data, sports analytics, play-by-play data, labeling platforms, and/or ML training platforms such as Union
Experience collaborating with CV engineers or integrating CV model outputs into downstream ML workflows
Experience using human review or correction workflows to evaluate and improve AI system quality
Experience building production systems in Rust
Familiarity with streaming, event-driven, audio/video, or real-time data workflows is a plus
Background or strong interest in sports, especially soccer, American football, and basketball

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4d ago

Analytics Engineer

FanDuel Jersey City, NJ

Jersey City, NJ

4d ago

$116k - $152k/yr Full time Analytics Big Data Business Intelligence

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Job Description

Responsibilities

Design, build, maintain, and enhance data models, datasets, and visualizations used by data scientists to drive business performance.
Bridge the data engineering team with data scientists, analysts, and stakeholders to leverage data for insights and decisions.
Develop pipelines for rapid, sometimes real-time, data ingestion into well-structured databases (SQL, Delta Lakes, etc.).
Maintain validation pipelines to flag bad or missing data and iterate as new databases are created.
Manage existing data transformation jobs for the Sports Modeling and Innovation team, optimize code across code bases, and troubleshoot issues.
Automate data cleaning projects on large datasets as part of ongoing database management.
Balance memory and speed tradeoffs to optimize project performance, aiming to reduce query times and prune unused metrics.
Create and own a backlog of Tableau dashboard and R Shiny app enhancements.
Curiosity about AI and emerging technologies is a plus.

Requirements

3+ years of experience in an analytics or data engineering role.
2+ years maintaining databases with a focus on improving data ingestion pipelines.
Deep understanding of relational databases.
Proficient in SQL, Databricks, R/Python, Tableau, AWS S3, and command line usage.
Experience building data pipelines using Python or R and Databricks is a strong advantage.
Bachelor's Degree, preferably in a numerate field (Math, Stats, Econ, etc.) or relevant data analysis experience.
Strong organizational and time-management skills.
Ability to work effectively in a fast-paced environment.
Solid problem-solving abilities and collaborative mindset.
Experience working on teams on collaborative projects.

Technologies

SQL
Delta Lakes
Databricks
R
Python
Tableau
AWS S3
Command Line
R Shiny

Benefits

Health plans
Fertility and family planning programs
Mental health support
Fitness benefits
Paid time off (PTO) and sick leave
Annual bonus and long-term incentive opportunities
401k with up to a 5% match
Commuter benefits
Pet insurance
FanDuel Total Rewards

Details

Location: Jersey City, NJ (onsite)
Salary: USD 116,000 - 152,250 per year
Education: Bachelor's Degree
Experience: 3+ years

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