Expert Statistical and Data Science Analysis of Lottery Historical Data

We are hiring a data scientist or statistician to perform a rigorous exploratory and probabilistic analysis of historical Brazilian lottery data (Mega-Sena and Lotofácil). This project is not about guaranteed predictions, “winning formulas”, or generic AI claims. Proposals that promise deterministic results or certainty will be automatically rejected.

Objective: To extract statistically sound insights from historical lottery data, including frequencies and distributions, correlations and co-occurrences, temporal patterns and probabilistic tendencies, and ranked probability outputs to support decision-making. The goal is analytical rigor and interpretability, not illusion of predictability.

Lottery Context: Mega-Sena: 6 numbers drawn from 1–60. Lotofácil: 15 numbers drawn from 1–25. Order does not matter and there is no repetition per draw. The output does not need to be restricted to official draw sizes. Expanded outputs such as top 8, 10 or 12 ranked numbers are acceptable and encouraged.

Methodological Expectations: The freelancer is free to choose methodologies, but relevant approaches may include - frequency and rolling-window analysis - gap and recurrence analysis - pair and triplet co-occurrence analysis - distribution and randomness tests - time-series exploration - Monte Carlo simulations - Markov or transition-based models - clustering and entropy analysis - exploratory machine learning models focused on ranking rather than deterministic prediction. All methods must be clearly explained and justified.

Validation is Mandatory: All findings must include - backtesting on historical periods - comparison against random baselines - explicit discussion of limitations, bias, and overfitting risks. Any result without validation will be considered incomplete.

Deliverables: - reproducible code (Python or R preferred) - visualizations such as charts, tables, and heatmaps - a final report explaining key insights, how to interpret results, practical implications, and what conclusions are not valid.

Proposal Evaluation Criteria: Proposals will be evaluated based on - statistical maturity and realism - depth and clarity of methodology - validation approach - clear definition of deliverables - ability to communicate results clearly - demonstrated experience in data analysis. Low-effort, buzzword-driven, or “AI magic” proposals will not be reviewed.

We will provide a spreasheet with the historical results of both lottery games