AI Sports Prediction Model Developer (College & Professional Sports

I am looking for an experienced AI/Machine Learning Engineer to build advanced predictive AI models for collegiate and professional sports. The goal is to develop a data-driven system that analyzes historical and real-time sports data to generate accurate predictions, rankings, probabilities, and actionable insights across multiple sports. I am looking for someone who can help design, build, test, and continuously improve the models over time. Sports Coverage The models should support multiple sports, including but not limited to: NCAA Football NCAA Men's & Women's Basketball NFL NBA MLB NHL Project Goals The AI models should be capable of: • Predicting game winners and win probabilities • Forecasting scores and scoring margins • Evaluating team and player performance • Identifying trends and matchup advantages • Incorporating historical and current-season statistics • Using injury reports, roster changes, schedules, and other relevant variables when available • Continuously improving as new data becomes available • Providing confidence scores for predictions • Supporting multiple predictive models to compare performance and improve accuracy Technical Requirements The ideal candidate should have experience with: • Python • Machine Learning • Predictive Modeling • Data Science • Sports Analytics • Statistics • Time-Series Forecasting • Feature Engineering • XGBoost, LightGBM, or similar algorithms • TensorFlow or PyTorch (preferred) • SQL • API integrations • Data engineering and ETL pipelines • FastAPI or Flask • Cloud deployment (AWS, Google Cloud, or Azure) • Git/GitHub Data Sources The system should be designed to ingest data from sports APIs and other licensed or publicly available data sources, including: • Team statistics • Player statistics • Historical game results • Advanced metrics • Injury reports • Schedules • Rankings • Weather (where applicable) • Betting market information (if incorporated into the analysis) Deliverables The selected freelancer will help: • Design the AI architecture • Build scalable machine learning models • Create automated data pipelines • Train and optimize prediction models • Evaluate model performance using objective metrics • Document the system and methodology • Provide recommendations for future improvements • Assist with deployment into a production-ready environment Ideal Candidate I'm looking for someone who has: • Experience building machine learning models from the ground up • Sports analytics or sports prediction experience • Strong statistical and data science skills • Excellent Python programming skills • Experience with large datasets and automation • Strong communication skills • The ability to work on a long-term project and continuously improve the models as new data becomes available Please include examples of similar AI, machine learning, predictive analytics, or sports analytics projects you've completed, along with links to your portfolio or GitHub if available.