Senior Real-Time Esports Data Scientist

GRID esports; Lisboa; Presencial; EUR 60 000 - 90 000; Tempo integral

Resumo da oferta

GRID esports in Lisbon is seeking a senior data scientist to design and deploy real‑time predictive models for esports betting markets. You will work end‑to‑end from research through live deployment, translating in‑game mechanics into robust features and models.

Join a team that values probabilistic thinking, backtesting rigor, and production‑grade Python code. Experience with real‑time data streams and MLOps tools is highly desired.

Qualificações

• 5+ years of professional experience in data science, quantitative research, or statistical modeling.
• Deep, intuitive understanding of probability, statistics, and machine learning theory.
• Expert‑level skills in the Python data stack. You write clean, production‑grade code.
• Proven experience designing complex backtesting environments and defining custom evaluation metrics for unique business problems.

Responsabilidades

• Design, build, and optimise ML models and statistical frameworks powering real‑time odds and betting markets.
• Extract predictive signals from raw esports telemetry, converting game mechanics into features.
• Focus on model performance and calibration; design backtesting to prevent data leakage and compare to historical baselines.
• Create mathematical rules translating base win probabilities into derivative markets like handicaps and player props.
• Ensure models are production‑grade and integrated into scalable pipelines and microservices.

Conhecimentos

5+ years experience

Probability & stats

Python production code

Backtesting frameworks

Ferramentas

Python

MLFlow

Airflow

Descrição da oferta de emprego

GRID esports in Lisbon is seeking a senior data scientist to design and deploy real‑time predictive models for esports betting markets. You will work end‑to‑end from research through live deployment, translating in‑game mechanics into robust features and models.

Join a team that values probabilistic thinking, backtesting rigor, and production‑grade Python code. Experience with real‑time data streams and MLOps tools is highly desired.