01/01/2026
HIRING: DATA ENGINEER
Objective:
Seeking an experienced Python developer to complete and enhance a real-time sports prediction platform. The application uses API-Sports data to forecast "up/down" outcomes across the four major U.S. sports leagues: NBA, NFL, MLB, and NHL. The goal is to deliver a modern, data-driven, and visually polished desktop/web application with advanced predictive capabilities.
🔧 Functional Modules
1. Data Integration
•Connect to API-Sports for real-time and historical data
• Normalize and store data across all four leagues
• Support player stats, team metrics, odds, and external conditions
• 2. Prediction Engine ( Already Working needs adjustment)
• Historical game data: win/loss records, point differentials, head-to-head, season phase
• Player metrics: injuries, fatigue, efficiency ratings (PER, WAR, QBR), lineup changes
• Team stats: offensive/defensive efficiency, turnover rates, special teams, bullpen, power play
• External conditions: weather, venue effects, travel schedules
• Market signals: betting odds, line movements, public vs sharp sentiment
• Forecasting models: logistic regression, Random Forest, XGBoost, LSTM/CNN, ensemble models
• Feature engineering: rolling averages, momentum indicators, normalized stats
• Monte Carlo simulation: thousands of outcome simulations, confidence intervals, calibration
• Validation & backtesting: cross-validation, ROC-AUC, simulated betting profitability
• Model Explainability (XAI): SHAP analysis to explain predictions (e.g., “Player injury: -5%”)
Pay: 40000-50000
Contact 03368468248
