data scientist

AIstats develops football analytics products powered by Machine Learning and Computer Vision, including a mobile app for fans and bettors and an analytics platform for football clubs, scouts, and agents.

• Develop and improve statistical and machine learning models;
• Analyze large-scale datasets using Python and SQL;
• Conduct statistical analysis, hypothesis testing, and experiment evaluation;
• Build interpretable ML solutions and explain model behavior;
• Collaborate with cross-functional teams on data-driven initiatives.

• 3+ Years of experience as a Data Scientist;
• Strong Python skills with NumPy, Pandas, and scikit-learn;
• Solid SQL knowledge;
• Strong understanding of probability theory and mathematical statistics;
• Experience with statistical testing: t-test, χ², ANOVA, Mann-Whitney, Wilcoxon, KS test, bootstrap/permutation tests, Bonferroni and FDR corrections;
• Hands-on experience with XGBoost, LightGBM, and CatBoost;
• Understanding of Bayesian methods;
• Experience with longitudinal/panel data, mixed/fixed/random effects models, and repeated measures;
• Experience with interpretable ML approaches: GAM, SHAP, partial dependence, counterfactual analysis;
• Nice to have: R, deep learning with Transformers, attention mechanisms and RNN/LSTM, Graph Neural Networks, Reinforcement Learning with PPO, MAPPO and MAT, Google Research Football or similar environments, advanced Bayesian statistics with PyMC, Stan, numpyro, MCMC and hierarchical models, causal inference with DAGs, instrumental variables and difference-in-differences, probabilistic spatial models including Markov chains, HMM/DBN, MRF/CRF and Gaussian processes.

• Fully remote work format;
• Flexible start of the working day and convenient schedule;
• Stable competitive salary pegged to the USD;
• 24 Days of paid vacation and 15 additional paid days off, including sick leave, corporate holidays, and national/religious holidays;
• Friendly communication culture, great product, and transparent processes;
• Dynamic work environment with a passionate team that loves sports and technology;
• Opportunities for professional growth and career development;
• No micromanagement, with trust, autonomy, and freedom to experiment.