Machine Learning Engineer (Sports Analytics)
609 USD 
We are looking for an ML developer for a sports analytics project.
The task is to build a model that will identify profitable strategies (value betting, outcome and odds analysis) based on betting data. The model already exists and was built by other people. I have their betting database for a specific bookmaker. Now we need to find ways to assemble the model from the existing database.
🔹 Responsibilities
- Data analysis of bets (football).
- Feature engineering (odds, line movements, leagues, time until the match, etc.).
- Training and testing models (scikit-learn, PyTorch/TensorFlow).
- Testing strategies on historical data (ROI, variance, drawdowns).
- Preparing an API/service that will provide signals for a future execution bot.
🔹 Data
- We provide access to accounts where real bets are placed.
- It is difficult to obtain historical data directly → either you will need to observe bets in real-time or help establish the process of collecting/parsing history.
🔹 Requirements
- Excellent knowledge of Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow).
- Experience with time series and probabilistic models.
- Ability to work with "dirty" data.
- Understanding of sports analytics and probabilities will be a plus.
🔹 We offer
- Interesting project at the intersection of ML and sports analytics.
- Long-term collaboration.
- Flexible schedule, remote work.
- Payment - negotiable (fixed or hourly).
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